{"paper_id":"3c2c2e2b-2026-4741-af8f-8b70bfe03fa2","body_text":"Uterine adenomyosis is a benign condition in which endometrium-like epithelial and stromal tissues appear in the myometrium, surrounded by hypertrophic smooth muscle. Similar to endometriosis and leiomyoma, adenomyosis is common in women of reproductive age 1 , 2 . Adenomyosis and endometriosis are closely linked diseases, as both are estrogen-dependent and often co-exist in the same patients 3 – 5 . This co-occurrence is a risk factor for relapse in women who have undergone fertility sparing surgery 6 – 8 .\nAlthough adenomyosis and endometriosis share some histological features and molecular changes 9 , there are notable differences in their pathogenesis, lesion localization, and clinical features 10 , 11 . For example, menorrhagia, recurrent implantation failure, and pregnancy loss are frequent in adenomyosis but not in endometriosis 12 , 13 . In addition, multiparity and prior uterine surgeries are linked to adenomyosis but not to endometriosis 14 . Thus, adenomyosis has come to be recognized as a distinct clinical entity.\nThe etiology of adenomyosis is currently unknown. Several theories for its development have been proposed, including direct invasion of endometriotic cells or an endometriotic lesion, metaplasia of displaced embryonic pluripotent Mullerian remnants, and differentiation of endometrial stem/progenitor cells 5 , 15 . In addition, despite the known differences between endometriosis and adenomyosis, Koninckx et al. 9  hypothesized in a recent review that a common molecular mechanism might underlie the pathogenesis of these disorders. However, no direct evidence to support this hypothesis exists at present, due to a lack of knowledge on the molecular mechanisms underlying adenomyosis pathogenesis.\nThe growth of an adenomyotic lesion is generally enhanced by estrogen and abrogated by progestogens. Adenomyotic symptoms are currently relieved using either endocrine therapies based on gonadotrophin-releasing hormone agonist (GnRHa) or progestins such as dienogest (DNG), or by employing a levonorgestrel-releasing intrauterine system (LNG-IUS) 16 , 17 . However, no formal guidelines for best medical management using these hormonal therapies exist 16 . Identification of the molecular underpinnings of adenomyosis could offer opportunities for precision treatment of this condition.\nNext-generation sequencing (NGS) is a powerful tool that permits the identification of somatic genomic alterations. Whereas mutations in  MED12  are frequent in leiomyoma (~70%) 18 , recurrent mutations in cancer-associated genes such as  KRAS ,  PIK3CA ,  ARID1A ,  PPP2R1A ,  PTEN , and/or  TP53  occur in uterine endometrial carcinoma 19 . Similarly, anatomical subtypes of endometriosis, such as ovarian endometrioma (EN-OV) and deep infiltrating (EN-DI) endometriosis, harbor mutations in  PIK3CA ,  ARID1A ,  PPP2R1A , and/or  KRAS 20 , 21 . Importantly,  PIK3CA - or  KRAS -mutated clones arising in histologically normal uterine endometrium have been proposed as the cellular origin of endometriosis 21 . However, very recent genomic analyses of normal human tissues, including endometrium, have undermined this hypothesis. RNA-sequencing analyses of 29 types of normal tissues, including the uterus, have uncovered the presence of expanded clones of cells with relatively high mutation burdens in many normal tissues 22 . Furthermore, endometrium samples from individuals who have undergone endometrial biopsy for a reason unrelated to endometriosis have frequently shown  KRAS  and  PIK3CA  mutations 23 , 24 . Thus, endometrial clones bearing  KRAS  and/or  PIK3CA  mutations may not necessarily drive the pathogenesis of endometriosis. Ideally, the status of  KRAS - and/or  PIK3CA -mutated clones in histologically normal endometrium (NE) should be compared between individuals with and without endometriosis. Accordingly, the exact contribution of  KRAS  and  PIK3CA  mutations to endometriosis remains unresolved.\nIn contrast to endometriosis, there has been, to date, no parallel genomic analysis of adenomyosis. Therefore, it is unknown whether adenomyosis involves clonal proliferation and whether its mode of molecular pathogenesis is shared with other gynecological disorders. This highlights the need for a comprehensive genomic characterization of adenomyosis to provide insights into many important and unresolved questions in adenomyosis etiology and pathology. To address this knowledge gap, we conduct NGS on a large panel of adenomyosis and co-occurring leiomyoma and endometriosis tissues. Our analyses reveal the presence of oligoclonality and recurrent  KRAS  mutations in adenomyosis tissues, and suggest that adenomyosis and endometriosis share molecular etiology, which may explain their frequent co-occurrence. Furthermore, we provide functional evidence for the role of mutant  KRAS  in mediating the efficacy of DNG as an adenomyosis therapy. Importantly, our findings could inform relapse risk assessment and therapeutic strategies for adenomyosis patients.\n\nTo define the molecular pathology of adenomyosis, we used NGS to characterize its genomic landscape. We collected fresh-frozen samples from 70 individuals: a discovery cohort of 51 adenomyosis patients whose samples were subjected to whole exome sequencing (WES), plus an additional 19 individuals who were biopsied at a later time and whose samples were subjected to targeted deep sequencing (TDS) (Supplementary Data  1  and  2 ). In 29 of these 70 individuals, multi-regional sampling of adenomyosis with/without co-existing endometriosis and leiomyoma was performed and adjacent normal tissues were collected (Supplementary Fig.  1  and Supplementary Data  3 ). In total, we banked fresh-frozen lesions of adenomyosis (192 specimens from 70 individuals), endometriosis (15 specimens from 10 individuals), leiomyoma (13 specimens from 10 individuals), ovarian cancer (5 specimens from 5 individuals), adjacent normal myometrial tissues (13 specimens from 12 individuals), and adjacent normal endometrial tissues (8 specimens from 6 individuals). As germline controls, we collected fresh-frozen peripheral blood or mononuclear cells from ascites (70 specimens from 70 individuals) (Supplementary Data  3 ). WES was performed on these samples with coverage of 130–170× for adenomyosis, endometriosis, leiomyoma, and ovarian cancer, and ~100× for adjacent and normal tissue samples (Supplementary Fig.  2  and Supplementary Data  4 ). Our robust criteria and validation by TDS (see Methods, Supplementary Fig.  3 , and Supplementary Data  5 ) permitted us to detect 134 unique synonymous and non-synonymous single-nucleotide variations (SNVs) in 31/51 (60.8%) adenomyosis cases (Supplementary Data  6 ), raising the possibility that adenomyosis is a clonal disorder with somatic mutations. These adenomyosis SNVs were present in low numbers (mean of 2.6 mutations/individual) and at low variant allele frequencies (VAF) (mean 4.8%; range 2.47–16.02%). These VAF values are comparable to those in co-occurring endometriosis but much lower than those in co-occurring leiomyoma and ovarian cancer (Fig.  1a, b , Supplementary Figs.  4  and  5 , and Supplementary Data  6 – 9 ). Fig. 1 Number and allele frequency of single-nucleotide variations (SNVs) identified in adenomyosis and co-occurring lesions. a  Number of somatic mutations in samples of adenomyosis ( n  = 51) and co-occurring cases of endometriosis ( n  = 7), leiomyoma ( n  = 8), and ovarian cancer ( n  = 5) presented as Tukey’s Box-and-Whisker plots.  b  Variant allele frequency (VAF) identified in the adenomyosis and co-occurring endometriosis, leiomyoma, and ovarian cancer samples in  a  presented as Tukey’s Box-and-Whisker plots.  c – e  Recurrence of the indicated gene mutations in adenomyosis ( c ), co-occurring endometriosis ( d ), and co-occurring leiomyoma ( e ). Top boxes: each box represents an individual SNV that was identified by whole exome sequencing (WES). SNVs were validated (grey) or not (white) by targeted deep sequencing (TDS). Middle boxes: samples were subjected to WES (purple) or TDS (yellow). Adenomyosis patients with co-occurring endometriosis (blue), leiomyoma (orange), and/or ovarian cancer (purple), and low progesterone receptor (PR) expression (black) are indicated above the patient number. Bottom boxes: each box represents an individual mutation of  KRAS  (red),  PIK3CA  (turquoise),  PPP2R1A  (blue), or  MED12  (brown).  f  VAF values for  KRAS  mutations in adenomyosis lesions (blue) or peripheral blood (red) as determined by TDS.  g  Schematic representation of somatic mutations in KRAS.\na  Number of somatic mutations in samples of adenomyosis ( n  = 51) and co-occurring cases of endometriosis ( n  = 7), leiomyoma ( n  = 8), and ovarian cancer ( n  = 5) presented as Tukey’s Box-and-Whisker plots.  b  Variant allele frequency (VAF) identified in the adenomyosis and co-occurring endometriosis, leiomyoma, and ovarian cancer samples in  a  presented as Tukey’s Box-and-Whisker plots.  c – e  Recurrence of the indicated gene mutations in adenomyosis ( c ), co-occurring endometriosis ( d ), and co-occurring leiomyoma ( e ). Top boxes: each box represents an individual SNV that was identified by whole exome sequencing (WES). SNVs were validated (grey) or not (white) by targeted deep sequencing (TDS). Middle boxes: samples were subjected to WES (purple) or TDS (yellow). Adenomyosis patients with co-occurring endometriosis (blue), leiomyoma (orange), and/or ovarian cancer (purple), and low progesterone receptor (PR) expression (black) are indicated above the patient number. Bottom boxes: each box represents an individual mutation of  KRAS  (red),  PIK3CA  (turquoise),  PPP2R1A  (blue), or  MED12  (brown).  f  VAF values for  KRAS  mutations in adenomyosis lesions (blue) or peripheral blood (red) as determined by TDS.  g  Schematic representation of somatic mutations in KRAS.\nAnalysis of the SNVs in adenomyosis cases revealed recurrent mutations encoding oncogenic KRAS p.G12 alterations (Patients #2, #3, and #6 in Supplementary Data  6 ). Patient #2 also harbored a mutation encoding the PPP2R1A p.R179 alteration observed in endometrial cancer and endometriosis. However, other mutations associated with uterine endometrial carcinoma and/or endometriosis (e.g.,  PIK3CA ,  ARID1A ,  PTEN , and  TP53 ) 19 – 21  were not identified in adenomyosis using our SNV criteria (Supplementary Data  6 ). We speculated that, confined by our criteria (mutant read number <8) (Supplementary Fig.  3 ), our WES coverage may not have been deep enough to detect alterations in these genes that had low VAF due to either minimal content or limited expansion of mutated adenomyosis clones. To sharpen our analysis, we examined the ClinVar database ( https://www.ncbi.nlm.nih.gov/clinvar/ ), a public database of pathogenic gene variations, to determine whether any registered pathogenic/driver mutations of  KRAS ,  PIK3CA ,  PPP2R1A ,  ARID1A ,  PTEN , and/or  TP53  were detectable in our adenomyosis WES data, including in the small number of mutant reads that had been filtered out by our SNV criteria. Using this strategy, we identified low numbers (<4) of pathogenic mutations of  KRAS ,  PIK3CA ,  PPP2R1A ,  ARID1A ,  TP53 , and  PTEN  in adenomyosis samples (Supplementary Data  10 ). To explore whether these candidate mutations were truly SNVs or pseudo-positives, we performed TDS on the adenomyotic lesions as well as on the corresponding germline control samples wherever possible. Although no mutation candidates in  ARID1A ,  TP53 , or  PTEN  were validated as somatic mutations in adenomyosis (Supplementary Data  11 ), this TDS analysis revealed recurrent somatic pathogenic mutations of  KRAS  and  PIK3CA  in this disease (Supplementary Data  12 ).\nWe next applied TDS analysis of  KRAS ,  PIK3CA , and  PPP2R1A  to not only the discovery cohort ( n  = 51; Fig.  1c , pink sequencing column) but also to the additional 19 adenomyosis patients (Fig.  1c , yellow sequencing column). Recurrent somatic pathogenic  KRAS  mutations, including 25 cases of alterations at G12 and 1 case at Q61, were identified in 37.1% (26/70) of adenomyosis cases (Figs.  1 c, f, g and Supplementary Data  12 ). Somatic mutations encoding the PIK3CA p.H1047 alteration were validated in lesions from Patients #1 and #27, as was a mutation encoding PPP2R1A p.P179 in a lesion from Patient #2 (Fig.  1c  and Supplementary Data  12 ). Based on these findings, we hypothesized that somatic  KRAS  mutation might be an important genomic alteration associated with adenomyosis. Consistent with published data 18 , 20 , 21 , samples of co-occurring endometriosis in some of our adenomyosis patients bore both  KRAS  and  PIK3CA  mutations (Fig.  1d  and Supplementary Data  12 ), whereas most co-occurring leiomyoma samples harbored  MED12  mutations (Fig.  1e ). Thus, the profiles of the dominant mutations linked to these three benign gynecological disorders differ.\nOnly a minor fraction of an adenomyosis lesion comprised epithelial cells (Fig.  2a ). This observation prompted us to consider whether the low VAFs we observed were due to low epithelial component content or limited clonal expansion of mutated cells. To isolate the epithelial component of adenomyosis samples, we performed laser capture microdissection (LCM) on formalin-fixed paraffin-embedded (FFPE) tissue samples from Patients #2, #6, and #8 (Fig.  2 b–e). We isolated genomic DNA from epithelial cells of adenomyosis tissue (LCM-A), as well as from adjacent muscle cells (non-diseased control; LCM-ADJ), and performed TDS. Compared with bulk frozen samples, VAFs were markedly increased in LCM-A (but not LCM-ADJ) samples from all three adenomyosis cases (Fig.  2 c–e, Supplementary Fig.  6 , and Supplementary Data  13 ), demonstrating that the low VAFs detected in our WES analyses of bulk frozen adenomyosis lesions were due to low epithelial component content rather than to poor expansion of mutated adenomyosis clones. These LCM experiments indicate that somatic mutation occurs in the epithelial component of adenomyosis, and that adenomyosis may thus arise from the ectopic proliferation of mutated epithelial cell clones. Fig. 2 Somatic mutations in the epithelial component of adenomyosis lesions. a ,  b  HE staining of epithelial cells from adenomyosis Patient #6 ( a ) before and ( b ) after isolation by laser capture microdissection (LCM). Scale bars, 100 μm.  c – e  Quantification of VAF as determined by TDS of the indicated genes in peripheral blood (Blood), frozen adenomyosis lesions (Bulk-A), LCM-acquired epithelial component of adenomyosis (LCM-A), or LCM-acquired adjacent muscle cells (LCM-ADJ) from the indicated patients.\na ,  b  HE staining of epithelial cells from adenomyosis Patient #6 ( a ) before and ( b ) after isolation by laser capture microdissection (LCM). Scale bars, 100 μm.  c – e  Quantification of VAF as determined by TDS of the indicated genes in peripheral blood (Blood), frozen adenomyosis lesions (Bulk-A), LCM-acquired epithelial component of adenomyosis (LCM-A), or LCM-acquired adjacent muscle cells (LCM-ADJ) from the indicated patients.\nTo initiate our investigation of clonal diversity within adenomyosis lesions, we performed multi-regional sampling and TDS of adenomyosis and co-existing leiomyoma lesions from Patients #28, #29, and #5. We detected multiple mutations in each lesion (Fig.  3 , Supplementary Figs.  7 – 9 , and Supplementary Data  14 – 16 ). Some mutations were shared among almost all multi-regional samples from a single patient (e.g.,  ZNF672  in Patient #28 (Fig.  3a );  C1QTNF  and  MSS51  in Patient #29 (Fig.  3b )), suggesting that these genetic alterations were acquired early during adenomyosis development, whereas other mutations were more restricted (Fig.  3 ). Most mutations detected in adenomyosis and co-existing leiomyoma were mutually exclusive (Figs.  3 b, c and  4a , and Supplementary Data  15 – 17 ), implying the lack of a clonal relationship between these disorders. Thus, despite their frequent co-occurrence, adenomyosis and leiomyoma are distinct entities. Fig. 3 Oligoclonality in adenomyosis tissues as revealed by multi-regional sampling. a  Left panel: coronal plane (top) and sagittal plane (bottom) schemes indicating the sites of multi-regional adenomyosis samples (1–6) and adjacent histologically normal myometrium (NM) that were acquired from Patient #28 and subjected to mutational profiling. R, right; L, left. Right panel: VAFs of mutations in the indicated genes in the indicated multi-regional samples profiled for each individual adenomyosis lesion, NM, or peripheral blood (B) sample from Patient #28. VAF values are shown using a color scale.  b ,  c  Top panels: sagittal plane schemes indicating the sites of multi-regional adenomyosis samples plus NM and leiomyoma (LM) samples that were acquired from Patient #29 ( b ) or Patient #5 ( c ) and subjected to mutational profiling. Bottom panels: analysis of VAFs for the samples in the top panels as for  a . For  a – c , raw VAF values (%) for each sample are shown in Supplementary Data  14 – 16 . Fig. 4 Multi-regional sampling reveals shared mutations in adenomyosis, endometriosis, and adjacent normal endometrium. Sagittal plane scheme (top) and VAF analysis (bottom) of sites of multi-regional adenomyosis (1–6) plus normal endometrium (NE), normal myometrium (NM), leiomyoma (LM), and blood (B) samples from Patient #8. VAF values are depicted as in Fig.  3 .  b ,  c  Coronal plane scheme (top) and VAF analyses (bottom) of multi-regional adenomyosis plus NE and/or NM samples from the indicated patients.  d – f  Coronal plane scheme (top), sagittal plane scheme (middle), and VAF analyses of multi-regional adenomyosis samples plus endometriosis samples (EN) and/or NM samples from the indicated patients. For  a – f , raw VAF values (%) for each sample are shown in Supplementary Data  17 – 19 .  g – i  Quantification of VAF values as determined by TDS of the indicated genes in frozen (Bulk) and LCM tissues from the indicated patients. Bulk tissues included peripheral blood (B), adenomyotic lesions (A), and endometriotic lesions (EN). LCM tissues included epithelial component of adenomyosis (A), endometriosis (EN), and normal adjacent tissues (ADJ). For  g – i , raw VAF values (%) for each sample are shown in Supplementary Data  21 .\na  Left panel: coronal plane (top) and sagittal plane (bottom) schemes indicating the sites of multi-regional adenomyosis samples (1–6) and adjacent histologically normal myometrium (NM) that were acquired from Patient #28 and subjected to mutational profiling. R, right; L, left. Right panel: VAFs of mutations in the indicated genes in the indicated multi-regional samples profiled for each individual adenomyosis lesion, NM, or peripheral blood (B) sample from Patient #28. VAF values are shown using a color scale.  b ,  c  Top panels: sagittal plane schemes indicating the sites of multi-regional adenomyosis samples plus NM and leiomyoma (LM) samples that were acquired from Patient #29 ( b ) or Patient #5 ( c ) and subjected to mutational profiling. Bottom panels: analysis of VAFs for the samples in the top panels as for  a . For  a – c , raw VAF values (%) for each sample are shown in Supplementary Data  14 – 16 .\nSagittal plane scheme (top) and VAF analysis (bottom) of sites of multi-regional adenomyosis (1–6) plus normal endometrium (NE), normal myometrium (NM), leiomyoma (LM), and blood (B) samples from Patient #8. VAF values are depicted as in Fig.  3 .  b ,  c  Coronal plane scheme (top) and VAF analyses (bottom) of multi-regional adenomyosis plus NE and/or NM samples from the indicated patients.  d – f  Coronal plane scheme (top), sagittal plane scheme (middle), and VAF analyses of multi-regional adenomyosis samples plus endometriosis samples (EN) and/or NM samples from the indicated patients. For  a – f , raw VAF values (%) for each sample are shown in Supplementary Data  17 – 19 .  g – i  Quantification of VAF values as determined by TDS of the indicated genes in frozen (Bulk) and LCM tissues from the indicated patients. Bulk tissues included peripheral blood (B), adenomyotic lesions (A), and endometriotic lesions (EN). LCM tissues included epithelial component of adenomyosis (A), endometriosis (EN), and normal adjacent tissues (ADJ). For  g – i , raw VAF values (%) for each sample are shown in Supplementary Data  21 .\nTo investigate whether the genomic alterations in adenomyosis originate in histologically NE and/or myometrium (NM), we compared mutations detected by TDS in multi-regional adenomyosis samples with those in adjacent NE/NM tissues (Fig.  4 a–c, Supplementary Figs.  10 – 12 , and Supplementary Data  17 – 19 ). Most mutations were detected only in adenomyotic lesions but some, including those of  KRAS  and  PIK3CA , also appeared in NE (e.g.,  SERPINA  in Fig.  4a ,  PIK3CA  in Fig.  4b , and  KRAS  in Fig.  4a, c ). Thus, these mutations likely arose in NE cells before they invaded the NM, consistent with a previously proposed etiology of endometriosis 21 . However, although adenomyosis frequently co-occurs with endometriosis, to date there has been no molecular evidence to support a common cellular origin. Significantly, we found identical  KRAS  mutations in co-existing adenomyotic and endometriotic lesions in multiple patients (Fig.  4 d–i, Supplementary Figs.  13  and  14 , and Supplementary Data  20  and  21 ). These results are in line with the frequent co-occurrence of endometriosis anatomical subtypes, such as EN-OV ( p  = 0.001; Table  1 ) and EN-DI ( p  = 0.0319; Table  1 ), in our cohort of  KRAS -mutated adenomyosis patients (Table  1  and Supplementary Data  22 ). Our data collectively raise the possibility that  KRAS -mutated clones arising in NE acquire enhanced invasiveness and proliferative capacity that enable them to grow ectopically, driving adenomyosis. Table 1 Relationship between patients’ characteristics and  KRAS  mutation status in adenomyosis. Characteristic KRAS  wild-type patient ( N  = 44) KRAS -mutated patient ( N  = 26) Median age at operation (range), years 42.5 (21–50) 41 (30–58) Preoperative treatment, no. (%) 25/44 (56.82) 19/26 (73.08) DNG, no. (%) 2/44 (4.55) 11/26 (42.31) GnRHa, no. (%) 23/44 (52.27) 9/26 (34.62) LNG-IUS, no. (%) 2/44 (4.55) 1/26 (3.85) PR-IHC Negative, no. (%) 7/44 (15.91) 13/26 (50) Disease co-occurrence Endometriosis, no. (%) 26/44 (59.09) 22/26 (84.62) EN-OV type, no.(%) 12/44 (27.27) 18/26 (69.23) EN-DI type, no.(%) 9/44 (20.45) 12/26 (46.15) EN-PE type, no.(%) 14/44 (31.82) 3/26 (11.54) Leiomyoma, no. (%) 28/44 (63.64) 13/26 (50.00) Ovarian cancer, no. (%) 0/44 (0.00) 5/26 (19.23) Endometrial cancer, no. (%) 0/44 (0.00) 1/26 (3.85) Cervical cancer, no. (%) 1/44 (2.27) 0/26 (0.00) MRI Endometrial subtype, no. (%) 5/44 (11.36) 1/26 (3.85) Subserous subtype, no. (%) 9/44 (20.45) 7/26 (26.92) Others (diffuse), no. (%) 28/44(63.64) 18/26 (69.23) Unknown, no. (%) 2/44 (4.55) 0/26 (0.00) History Caesarean section, no. (%) 5/44 (11.36) 0/26 (0.00) Dilatation and curettage, no. (%) 13/44 (29.55) 7/26 (26.92) Vaginal delivery, no. (%) 5/44 (11.36) 8/26 (30.77) Abortion or stillborn, no. (%) 17/44 (38.64) 10/26 (38.46) Premature birth, no. (%) 1/44 (2.27) 2/26 (7.69) Hysterectomy, no. (%) 16/44 (36.36) 15/26 (57.69) Gravidity, no. (%) 23/44 (52.27) 14/26 (53.84) Smoking history, no. (%) 8/44 (18.18) 3/26 (11.54) DNG  dienogest,  EN-DI  deep infiltrating endometriosis,  EN-OV  ovarian endometrioma,  EN-PE  peritoneal endometriosis,  GnRHa  gonadotrophin-releasing hormone agonist,  PR-IHC  immunohistochemistry of progesterone receptors shown in Fig.  7 ,  LNG-IUS  levonorgestrel-releasing intrauterine systems\nRelationship between patients’ characteristics and  KRAS  mutation status in adenomyosis.\nDNG  dienogest,  EN-DI  deep infiltrating endometriosis,  EN-OV  ovarian endometrioma,  EN-PE  peritoneal endometriosis,  GnRHa  gonadotrophin-releasing hormone agonist,  PR-IHC  immunohistochemistry of progesterone receptors shown in Fig.  7 ,  LNG-IUS  levonorgestrel-releasing intrauterine systems\nAs noted above, recent reports have revealed frequent  KRAS  and  PIK3CA  mutations in NE, i.e., in uterine endometrium that are histologically normal and unaffected by endometriosis or adenomyosis 23 , 24 . We also detected these mutations in NE adjacent to adenomyotic lesions, prompting us to investigate the relevance of  KRAS - and  PIK3CA -mutated clones to the molecular pathogenesis of adenomyosis. To this end, we examined whether the frequency of these mutations was altered in NE adjacent to an adenomyotic lesion. We collected either fresh-frozen or FFPE samples of uterine tissue from 56 individuals: 18 individuals with adenomyosis (group A), 14 individuals with endometriosis but not adenomyosis (group E), and 24 individuals with neither endometriosis nor adenomyosis (group Non-A/E) (Supplementary Data  23  and  24 ). After enrichment by macro-dissection, samples of NE and adjacent NM (control) for each individual were subjected to TDS, to assess  KRAS ,  PIK3CA , and  PPP2R1A  status (Fig.  5 ). Among macro-dissected NE samples,  KRAS  mutations were commonly observed in group A (10/18 = 55.6%) and group E (7/14 = 50%), but less frequently in group Non-A/E (7/24 = 29.1%) (Fig.  5a  and Supplementary Data  24 – 26 ) as determined by our mutation criteria (see Methods). Mutations in  PIK3CA  were also observed but to a lesser extent: group A (2/18 = 11.1%), group E (5/14 = 35.7%), and group Non-A/E (6/24 = 25%) (Fig.  5a  and Supplementary Data  23 – 25 ). These observations are consistent with recent publications showing that recurrent  KRAS  and  PIK3CA  mutations can occur in the endometrium that appears to be histologically normal 23 , 24 . Next, we compared the VAFs of  KRAS ,  PIK3CA  and  PPP2R1A  hotspot mutations in the macro-dissected NE of group A vs. group E vs. group Non-A/E (Fig.  5b  and Supplementary Data  26 ). Importantly, the VAFs of mutations encoding oncogenic KRAS p.G12/G13 alterations (but no other mutations) were significantly enhanced in group A (mean value: 1.641%) compared with group Non-A/E (0.301%) ( p  = 0.008; Fig.  5b  and Supplementary Data  26 ), suggesting that  KRAS -mutated clones had expanded in NE of individuals with adenomyosis. We found that  KRAS  mutations were not significantly more frequent in samples from group A ( p  = 0.117) and group E ( p  = 0.297) than in those from group Non-A/E (Fig.  5a ). However, our VAF analysis revealed a statistically significant increase in  KRAS -mutated clones in group A compared with group Non-A/E ( p  = 0.008) (Fig.  5b ). Follow-up in a suitably large number of additional patient samples is required, but if corroborated, the latter result suggests our hypothesis that an increase in the frequency of  KRAS -mutated clones in NE might be the origin of adenomyosis. Taken together, these genomic analyses of NE suggest that an increase in expanded  KRAS -mutated clones in this tissue may be an early step in the molecular pathogenesis of adenomyosis. Fig. 5 Increased mutation frequency and VAF of  KRAS -mutated clones in the histologically normal endometrium adjacent to adenomyotic or endometriotic lesions. a ,  b  Histologically normal myometrium (NM; negative control) and endometrium (NE) were macro-dissected from the indicated three groups of patients.  a  Occurrence of the indicated gene mutations in NE of patients with adenomyosis (patient ID column: orange), patients with neither adenomyosis nor endometriosis (patient ID column: yellow), and patients with endometriosis but without co-occurring adenomyosis (patient ID column: purple). Bottom boxes: each box represents an individual mutation of  KRAS  (red),  PIK3CA  (turquoise), or  PPP2R1A  (blue). VAF values are shown using individual color scales.  b  Quantification of VAF values as determined by TDS of the indicated mutations in the macro-dissected NM (negative control) or NE from the patients in the group A (adenomyosis; orange in  a ), group Non-A/E (patients with neither adenomyosis nor endometriosis; yellow in  a ), and group E (patients with endometriosis but without co-occurring adenomyosis; purple in  a ). Source data are provided as a  Source Data  file. Data are values for individual patients plus the mean. * p   <  0.05 by Welch’s  t -test.\na ,  b  Histologically normal myometrium (NM; negative control) and endometrium (NE) were macro-dissected from the indicated three groups of patients.  a  Occurrence of the indicated gene mutations in NE of patients with adenomyosis (patient ID column: orange), patients with neither adenomyosis nor endometriosis (patient ID column: yellow), and patients with endometriosis but without co-occurring adenomyosis (patient ID column: purple). Bottom boxes: each box represents an individual mutation of  KRAS  (red),  PIK3CA  (turquoise), or  PPP2R1A  (blue). VAF values are shown using individual color scales.  b  Quantification of VAF values as determined by TDS of the indicated mutations in the macro-dissected NM (negative control) or NE from the patients in the group A (adenomyosis; orange in  a ), group Non-A/E (patients with neither adenomyosis nor endometriosis; yellow in  a ), and group E (patients with endometriosis but without co-occurring adenomyosis; purple in  a ). Source data are provided as a  Source Data  file. Data are values for individual patients plus the mean. * p   <  0.05 by Welch’s  t -test.\nMany adenomyotic patients initially receive hormonal treatment, including administration of the PR agonist DNG 17 , 25 . Those patients who do not respond to such hormonal treatment then undergo surgery. Our analyses revealed intriguing clinical differences between cases of adenomyosis with  KRAS  mutations vs. those without. Specifically,  KRAS  mutations were more frequent in lesions of patients who had been pretreated with DNG (84% (11/13)) compared with non-pretreated patients (26% (15/57);  p  = 0.0002), a difference not found in patients treated with GnRHa (Table  1  and Supplementary Data  22 ). This observation generates two hypotheses as follows: (1) DNG may be less efficacious in patients bearing  KRAS -mutated adenomyotic clones, allowing these abnormal cells to persist until surgery; and (2) DNG treatment drives an enrichment of  KRAS  mutations in adenomyosis. We next sought to distinguish between these two possibilities. DNG reportedly exerts an anti-proliferative effect on cells of the epithelial component of adenomyosis 26 . We examined the effect of mutated  KRAS  expression on DNG’s ability to suppress proliferation by taking advantage of an immortalized uterine endometrial epithelial cell line. We engineered these cells to overexpress wild type KRAS ( KRAS -WT), mutated KRAS ( KRAS -Mut; G12C or G12D), PIK3CA-WT, or mutated PIK3CA ( PIK3CA -Mut; E545K or H1047R), and then assessed their viability and proliferation following exposure to DNG (Fig.  6 a–c). We observed that a greater percentage of DNG-treated immortalized endometrial cells expressing  KRAS -Mut were viable compared to empty vector-transfected controls (Fig.  6b ). Furthermore, analysis of BrdU incorporation showed that  KRAS -Mut expression abrogated DNG’s ability to suppress cell proliferation (Fig.  6c ). In contrast, expression of mutated  PIK3CA  in immortalized cells had no effect on DNG efficacy (Fig.  6 b, c). Thus, expression of mutated  KRAS  interferes with DNG’s ability to reduce cell proliferation. Taken together, these data support our hypothesis #1 ( KRAS -mutated adenomyotic clones are less sensitive to DNG treatment) rather than hypothesis #2 (DNG drives  KRAS  mutations in adenomyosis patients). However, it should be noted that future follow-up studies using an appropriately sized cohort will be necessary to reach a definitive conclusion. Fig. 6 Mutant  KRAS  expression abrogates the progestin-induced anti-proliferative effect of DNG through downregulation of  PR . a  Immunoblotting to detect ectopically expressed, HA-tagged wild-type (WT) KRAS and PIK3CA, or KRAS or PIK3CA bearing the indicated amino acid substitutions, in immortalized human uterine epithelial cells. Vinculin, loading control. Viability ( b ) and proliferation ( c ) of WT immortalized uterine endometrial epithelial cells or those overexpressing the indicated mutations of  KRAS  or  PIK3CA .  b  Cells were exposed to 1 μM DNG or vehicle (DMSO) for 72 h. Results are the percentage of viable cells relative to vehicle control cells. Data are the mean + SD of six independent experiments, each with three technical replicates per group. * p   <  0.05 by Welch’s  t -test.  c  Cells were exposed to 1 μM DNG or vehicle (DMSO) for 48 h. Results are the percentage of BrdU +  cells relative to vehicle control cells. Data are the mean + SD of four independent experiments per group without technical replicates. * p   <  0.05 by Welch’s  t -test.  d  Quantitative RT–PCR determination of mRNA levels of  PR - A/B  in the immortalized cells in  a . Values were normalized to  GAPDH . Data are the mean fold change + SD relative to levels in control cells stably infected with empty vector. Six independent experiments, each with three technical replicates per group, were conducted. * p   <  0.05 by Welch’s  t -test. Source data are provided as a  Source Data  file.\na  Immunoblotting to detect ectopically expressed, HA-tagged wild-type (WT) KRAS and PIK3CA, or KRAS or PIK3CA bearing the indicated amino acid substitutions, in immortalized human uterine epithelial cells. Vinculin, loading control. Viability ( b ) and proliferation ( c ) of WT immortalized uterine endometrial epithelial cells or those overexpressing the indicated mutations of  KRAS  or  PIK3CA .  b  Cells were exposed to 1 μM DNG or vehicle (DMSO) for 72 h. Results are the percentage of viable cells relative to vehicle control cells. Data are the mean + SD of six independent experiments, each with three technical replicates per group. * p   <  0.05 by Welch’s  t -test.  c  Cells were exposed to 1 μM DNG or vehicle (DMSO) for 48 h. Results are the percentage of BrdU +  cells relative to vehicle control cells. Data are the mean + SD of four independent experiments per group without technical replicates. * p   <  0.05 by Welch’s  t -test.  d  Quantitative RT–PCR determination of mRNA levels of  PR - A/B  in the immortalized cells in  a . Values were normalized to  GAPDH . Data are the mean fold change + SD relative to levels in control cells stably infected with empty vector. Six independent experiments, each with three technical replicates per group, were conducted. * p   <  0.05 by Welch’s  t -test. Source data are provided as a  Source Data  file.\nDNG is a PR agonist, which prompted us to examine PR protein levels in  KRAS -mutated adenomyosis. We performed immunohistochemical analyses to estimate PR protein levels in the epithelial component of adenomyosis lesions from all 70 of our adenomyosis patients (Fig.  7 , Table  1 , and Supplementary Data  22 ). A decrease in PR protein specifically in the epithelial component was significantly more frequent in samples from patients with  KRAS- Mut (13/26; 50%) than in samples from patients with  KRAS -WT (7/44; 15.91%) ( p  = 0.052; Table  1 ). Strikingly, these findings recapitulate those reported for endometrial cancer 27 . Fig. 7 Downregulation of progesterone receptors (PRs) in  KRAS -mutated adenomyosis as assessed by immunohistochemical (IHC) analyses. Representative photomicrographs of (upper) IHC of PR and (lower) HE staining of adenomyotic lesions from the indicated patients. Arrowheads, epithelial component. Scale bars, 100 µm.\nRepresentative photomicrographs of (upper) IHC of PR and (lower) HE staining of adenomyotic lesions from the indicated patients. Arrowheads, epithelial component. Scale bars, 100 µm.\nThere are two major  PR  isoforms,  PR - A  and  PR - B , which are transcribed from different promoters in a single gene 28 . To investigate whether the reduced PR protein in  KRAS -mutated adenomyosis samples was due to an effect of mutant KRAS on  PR  mRNA expression, we applied qPCR analysis to our immortalized endometrial cells overexpressing  KRAS -Mut,  KRAS -WT,  PIK3CA -WT, or  PIK3CA -Mut (please see the  Source Data  file). We found that  PR - A/B  mRNAs were indeed downregulated in cells expressing  KRAS -Mut but not in those expressing  KRAS -WT,  PIK3CA -WT, or  PIK3CA -Mut (Fig.  6d ). Although these in vitro overexpression data derived from a single cell line do not show whether  KRAS  mutation downregulates  PR  mRNA directly or indirectly, they suggest that  KRAS -Mut is linked to downregulation of  PR  expression. Further experiments employing additional independent cell lines and/or patient-derived primary cultures should be conducted in the future to validate these results.\nLastly, we sought to determine how  PR  downregulation by  KRAS -Mut might be achieved. Expression of  PR - A/B  is known to be regulated, at least in part, by methylation of the  PR  gene promoters 28 – 30 . In endometriosis, epigenetic silencing of  PR-A/B  imposed by increased methylation of CpG islands within exon 1 has been observed 29 . To investigate whether increased DNA methylation was involved in downregulating  PR  in  KRAS -Mut adenomyosis, we performed bisulfite sequencing of DNA from the enriched epithelial component of adenomyotic lesions from PR-expressing  KRAS -WT samples ( n  = 20) and from all 13 PR-negative  KRAS -Mut samples. In PR-expressing  KRAS -WT adenomyosis, no significant DNA methylation of CpG islands in the  PR - A / B  promoters was detected (Fig.  8  and Supplementary Data  27 ). In contrast, there was a marked increase in the methylation level of the  PR-A/B  promoters in  KRAS -Mut adenomyosis. These results suggest that epigenetic silencing may contribute to the  PR  downregulation observed in  KRAS -mutated adenomyosis, and that DNG may be less effective in treating  KRAS -mutated adenomyosis due to this suppression of  PR - A / B  expression. Fig. 8 Mutant  KRAS  expression is linked to epigenetic silencing of  PR . a  Schematic diagram of the  PR - A/B  promoters and exon 1. Transcription start sites (arrows), CpG islands, and regions of bisulfite sequencing are indicated.  b  Frequency of methylated CpG in  PR - B  (top) and  PR-A  (bottom) as determined by bisulfite sequencing of DNA from  KRAS -WT ( n  = 20) and  KRAS -mutated ( n  = 11) adenomyosis samples. Data are the mean + SD. * p   <  0.05 by Welch’s  t -test.\na  Schematic diagram of the  PR - A/B  promoters and exon 1. Transcription start sites (arrows), CpG islands, and regions of bisulfite sequencing are indicated.  b  Frequency of methylated CpG in  PR - B  (top) and  PR-A  (bottom) as determined by bisulfite sequencing of DNA from  KRAS -WT ( n  = 20) and  KRAS -mutated ( n  = 11) adenomyosis samples. Data are the mean + SD. * p   <  0.05 by Welch’s  t -test.\n\nOur NGS-based study provides fresh insights into the pathogenesis of adenomyosis. We have shown that: (i)  KRAS -mutated adenomyotic clones originate from NE (Fig.  4 a–c); (ii)  KRAS  mutations are shared by co-occurring adenomyosis and endometriosis lesions (Fig.  4 d–i); and (iii) the presence of  KRAS  mutations in adenomyosis is associated with the co-occurrence of endometriosis (Table  1  and Supplementary Data  22 ). Although inflammation caused by ectopic proliferation of epithelial cells and/or de novo metaplasia may play a role in the genetic alterations and disease pathogenesis in some adenomyosis patients, our data suggest that both adenomyotic and endometriotic clones can arise from NE, explaining the high frequency of co-occurrence of these disorders. Nevertheless, we did find evidence of clonal heterogeneity in their development. In Patients #6 and #24, the adenomyotic and endometriotic lesions contained different  KRAS  mutations (Figs.  4f, i , Supplementary Figs.  15  and  16 , and Supplementary Data  20  and  28 ). Non- KRAS  mutations may also be involved in some cases, as Patient #4 exhibited the same  HIPK1  alteration in her  KRAS -WT adenomyotic and endometriotic lesions (Supplementary Figs.  15 C–D and  17 , and Supplementary Data  29 ).\nRecent genomic analyses have shown that histologically NE can bear a relatively high burden of mutations that includes recurrent  PIK3CA  and  KRAS  alterations 23 , 24 . Consistent with these observations, we also detected recurrent  PIK3CA  and  KRAS  mutations in individuals without adenomyosis or endometriosis (Fig.  5a ). However, the frequency and VAF of such mutated clones were significantly elevated in adenomyosis samples (Fig.  5b ), suggesting that additional alterations in  KRAS -mutated clones in the NE might occur very early during the molecular pathogenesis of adenomyosis. Although our study did not definitively identify a common or first event of genetic and/or epigenetic alteration establishing NE clonality, from a mechanistic point of view,  KRAS  or  PIK3CA  mutation would be considered likely to provide NE cell clones with the ability to proliferate and invade neighboring NM and/or other organs, driving the development of adenomyosis. Mutations of  MED12  and/or  FH , which are common in leiomyoma and show high VAFs, have been reported in ~10% of adenomyosis and adenomyotic polyps 31 , 32 . However, for unknown reasons, these alterations were not detected in our NGS analyses of our adenomyosis cohort (Supplementary Data  6  and  15 – 17 ). Lastly, the burdens of total and cancer-associated mutations are known to become elevated in NE by ageing and high body mass index 24 . Although age did not correlate with frequency of  KRAS  mutations in our cohort (Supplementary Data  25 ), it would be intriguing to determine whether these factors are also relevant in the contexts of adenomyosis and endometriosis, a question demanding future studies using a larger patient cohort.\nRelapses of endometriosis and adenomyosis are relatively common 6 , 33  and co-existence of adenomyosis and endometriosis increases relapse risk 3 , 6 , 7 . Our mutational characterization suggests that both of these disorders originate from NE, raising the concern that patients receiving uterus-sparing cytoreductive surgery face a significant relapse risk. Over the past decade, DNG has proven effective for treatment of endometriosis and has been approved for such. However, DNG has also been used for treatment of adenomyosis-related symptoms 26 , 30 , despite a lack of formal knowledge of its side-effects and efficacy in this context. Indeed, efficacy of DNG in treating adenomyosis reportedly varies by individual, in contrast to treatment with GnRHa 34 , 35 . Although DNG potentially has the advantages of relatively long-term efficacy and oral administration, there is currently no proper therapeutic management protocol for its use in treating adenomyosis 16 . Our work using an immortalized cell system in vitro has suggested that adenomyotic lesions frequently contain  KRAS  mutations that may epigenetically downregulate  PR  and thus reduce DNG efficacy. This observation should be followed up in a large number of DNG-treated adenomyosis patients to determine if our hypothesis is valid and if its implications are translatable to the clinic.\nIn our cohort of adenomyosis patients, pretreatment with LNG-IUS, an intrauterine device producing local progestin, showed no outcome correlation with the presence of  KRAS  mutations (Table  1 ). We speculate that this discrepancy could be due to differences in the effective concentration of progestin delivered to the uterus by local (LNG-IUS) vs. oral (DNG) administration. It may also be relevant that only three LNG-IUS patients were available for our analysis. In any case, at least for oral DNG therapy,  KRAS  status may be a biomarker of treatment efficacy, and testing a needle biopsy of an adenomyosis lesion for  KRAS  mutation and/or PR expression might be a valuable diagnostic option. Obviously, further investigations are required to establish the validity of this approach, but investigation of the  KRAS  and  PIK3CA  mutation status of non-diseased uterine tissue of adenomyosis patients might greatly aid in surgical decision-making and therapeutic management.\n\nPatients with adenomyosis gave written informed consent prior to their participation in this study. This project was approved by the institutional ethics committees of the University of Tokyo (Project Number  G10035 ), the Juntendo University Faculty of Medicine (Project Number 2014176), and the National Cancer Center Research Institute (Project Number 2015–202). The establishment of this cell line was approved by the Ethics Committees of the National Cancer Center and Nagoya University, and the subject gave informed consent for the use of her clinical samples. Tissue samples from patients with adenomyosis were obtained at the University of Tokyo Hospital and Juntendo University Hospital between December 2016 and July 2019. All patients underwent magnetic resonance imaging for diagnostic purposes. Adjacent normal tissues, which were grossly and tactically distinguishable from adenomyotic lesions, were collected during surgery. Histological review by the study pathologist confirmed that there was no significant contamination of normal tissue by adenomyotic cells. See also Supplementary Data  1  and  2 , and  22 – 24  for additional clinical details pertaining to these specimens.\nWith respect to therapies, prior to surgery, patients with adenomyosis underwent treatment with GnRHa, DNG, or LNG-IUS according to their symptoms. GnRHa was mainly used to improve blood hemoglobin levels in patients with severe anemia due to heavy menstrual bleeding (HMB). For GnRHa treatment, subcutaneous injection of 1.88 mg leuprorelin acetate or 1.8 mg goserelin acetate was initiated during menstruation and repeated every 4 weeks. DNG was used to relieve symptoms in patients with dysmenorrhea alone, whereas LNG-IUS was used for those with dysmenorrhea and HMB. For DNG, daily oral administration of 2 mg was started on days 2–5 of menstruation. For LNG-IUS, 52 mg LNG was inserted into the uterine cavity on day 7 of menstruation.\nLesions and adjacent normal tissues were obtained from surgically resected specimens, immediately frozen after resection (fresh-frozen), and stored at −80 °C. Samples of peripheral blood and/or monocytes from ascites fluid were stored at −30 °C. See Supplementary Data  3  for additional sample information.\nGenomic DNA was extracted from specimens using the QIAamp DNA Blood Midi Kit or the QIAamp Fast DNA Tissue Kit (Qiagen) and quantified by Nanodrop (Thermo Fisher). Fragmentation of genomic DNA was performed using a Covaris LE220 sonicator to produce fragments of ~200 bp and sequencing libraries were generated using the NEBNext Ultra DNA Library Prep kit for Illumina (New England BioLabs). Exonic fragments were enriched with the SureSelect Human All Exon Kit v6 (Agilent Technologies) and paired-end libraries were analyzed and quantified using 2200Tapestation (Agilent Technologies) and a Qubit Fluorometer (Invitrogen). Massively parallel, paired-end sequencing of sample libraries was performed with a HiSeq2500 sequencer (Illumina) as previously described 36  (Supplementary Data  4 ).\nWES reads were independently aligned to the human reference genome (hg38) using BWA, Bowtie2 ( http://bowtie-bio.sourceforge.net/bowtie2/index.shtml ), and NovoAlign ( http://www.novocraft.com/products/novoalign/ ). Both somatic synonymous and non-synonymous mutations were called using three publicly available mutation callers: MuTect ( http://www.broadinstitute.org/cancer/cga/mutect ), SomaticIndelDetector ( http://www.broadinstitute.org/cancer/cga/node/87 ), and VarScan ( http://varscan.sourceforge.net ). Mutations were discarded if any of the following criteria were met: the total read number was <100, the mutant read number was <7, the VAF in disease samples was <0.024, the VAF in the germline control samples was >0.01, the mutation occurred in only one strand of the genome, or the variant was present in normal human genomes in either the 1000 Genomes Project dataset ( http://www.internationalgenome.org/ ) or our in-house database. Gene mutations were annotated by SnpEff ( http://snpeff.sourceforge.net ). To this end, genomic DNA samples from adenomyosis tissues and corresponding germline controls were subjected to TDS (see details below). Over 100 targets were evaluated in this validation experiment, allowing us to establish criteria that eliminated 95.4% of validated false-positive calls at the expense of only 15.4% of validated true positive calls (Supplementary Fig.  3 ).\nGenomic regions (~250 bp) containing candidate mutated bases were PCR-amplified using appropriate primer sets (Supplementary Data  5 ). PCR products were purified using AMPure beads (Beckman) and subjected to library construction using the NEBNext Ultra DNA Library Prep Kit for Illumina (New England BioLabs). Libraries were sequenced on an Illumina Miseq using Reagent Kit V2 (300 cycles) to generate 150 bp paired-end reads.\nAs the VAF values of the observed mutations in adenomyosis were quite low, we performed a statistical calculation to determine whether these alterations were true somatic mutations or NGS noise. In general, it is expected that the distribution of the difference in VAFs between lesion and control samples follows a normal distribution. For each position  i , a difference of VAFs between adjacent ( a ) and normal ( n ) is defined by  \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$d_i = \\max _{y \\in {\\mathrm{\\Sigma }}}|a_{y,i} - n_{y,i}$$\\end{document} d i = max y ∈ Σ ∣ a y , i − n y , i , where Σ is the set of nucleotides  \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\left\\{ {A,C,G,T} \\right\\}$$\\end{document} A , C , G , T . Let  \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\mu _j$$\\end{document} μ j  and  \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\sigma _j$$\\end{document} σ j  be the mean (shown in column M in Supplementary Data  12  and column L in Supplementary Data  14 – 20  and  28 – 29 ) and the SD (shown in column N in Supplementary Data  12  and column M in Supplementary Data  14 – 20  and  28 – 29 ), respectively, of the set  \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\left\\{ {d_k|k = j - K, \\ldots ,j - 1,j + 1, \\ldots ,j + K} \\right\\}$$\\end{document} d k ∣ k = j − K , … , j − 1 , j + 1 , … , j + K  for the estimated position  j . If one assumes that  \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$X\\sim N(\\mu _j,\\sigma _j^2)$$\\end{document} X ~ N ( μ j , σ j 2 ) , then the somatic mutation rate for  j  is defined by  \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$P\\left( {X > d_j} \\right) < 0.05$$\\end{document} P X > d j < 0.05 ,  \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$d_j > 0.001$$\\end{document} d j > 0.001  and  \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$n_{y,j} < 0.01$$\\end{document} n y , j < 0.01 , where  \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$y \\in {\\mathrm{\\Sigma }}$$\\end{document} y ∈ Σ . For  K  values, we used the values shown in length (bp) (column O in Supplementary Data  12  and column N in Supplementary Data  14 – 20  and  28 – 29  for the individual mutation analyses). For assessment of statistical significance of somatic mutations, the  p -value of each mutation is shown in column P in Supplementary Data  12  and column O in Supplementary Data  14 – 20  and  28 – 29 .\nFFPE tissue samples were sectioned at 8–10 μm thickness, mounted on polyethylene naphthalate membrane-coated slides (Leica Microsystems), and stained with hematoxylin (Sakura Fineteck) for 1 min and eosin (Sakura Fineteck) for 30 s. The epithelial components of adenomyosis and adjacent normal muscle tissues were separately micro-dissected using an LMD 7000 instrument (Leica Microsystems) as directed by the study pathologist (T.H.S.). Genomic DNA was extracted using the QIAamp DNA FFPE Tissue Kit or QIAamp DNA micro Kit (Qiagen) and subjected to PCR, to amplify candidate mutations using the primers listed in Supplementary Data  5 . For direct sequencing, PCR products were purified using a PCR purification kit (Qiagen) and sequenced using an Applied Biosystems 3130 Genetic Analyzer (Applied Biosystems). For TDS, PCR products were purified using AMPure beads and subjected to library construction using the NEBNext Ultra DNA Library Prep Kit (New England BioLabs). Paired-end sequencing (150 bp) was conducted on an Illumina Miseq instrument using Reagent Kit V2 (300 cycles).\nFresh-frozen samples were embedded in OCT compounds (Sakura), sectioned at 10 μm thickness using a Cryostat CM3000 (Leica Microsystems), and mounted on slide glasses (Matsunami Glass IND. Ltd). FFPE tissue samples were sectioned at 10 μm thickness and mounted on the slide glasses. After hematoxylin and eosin staining, NM and epithelial component of histologically normal NE were macro-dissected under microscope. Genomic DNA was extracted using GeneRead DNA FFPE Kit (Qiagen) and quantified by Qubit fluorometer (Thermo Fisher). TDS analyses were described above. See Supplementary Data  23  for patient and sample information. As peripheral blood samples were not available for the FFPE tissue samples, we had to use histologically normal (NM) tissue samples as a negative control. Most SNVs, including  KRAS  and  PIK3CA  mutations, were only detected in NE but not NM (Fig.  2–4  and Supplementary Data  14 – 21 ). As the VAFs of the mutations in the macro-dissected epithelial component of NE were low (Fig.  5b ), we considered an alteration in a sample as a true mutation if its VAF was higher than the mean VAF + 3 SD in the 56 NE samples (Supplementary Data  26 ). The cutoffs for the SNV are as follows: 0.335% (mean: 0.065%, SD: 0.09%) for KRAS p.G12/G13, 0.302% (mean: 0.05%, SD: 0.084%) for KRAS p.Q61, 0.127% (mean: 0.043%, SD: 0.028%) for PIK3CA p.E542E545, 0.158% (mean: 0.032%, SD: 0.042%) for PIK3CA p.H1047, and 0.15% (mean: 0.042%, SD: 0.036%) for PPP2R1A p.R179-R183.\nAdenomyosis samples were fixed in 4% paraformaldehyde (Pierce) at 4 °C for 24 h. Paraffin sections (5 μm) were subjected to immunostaining with anti-progesterone receptor antibody (undiluted; clone: 1E2; Ventana) using the Benchmark XT automated staining system (Roche). Scoring of all PR immunostaining was performed blind by T.H.Y. to avoid evaluator bias.\nGenomic DNA from LCM-enriched adenomyotic lesions was subjected to bisulfite conversion using an EpiTect Bisulfite Kit (Qiagen). Converted DNA samples were amplified by PCR using a Kapa HiFi Uracil +  Kit (Kapa Biosystems). All procedures were performed according to the manufacturer’s instructions. The bisulfite converted genomic DNA were subjected to the PCR; 98 °C for 5 min followed by 50 cycles of 98 °C for 10 s, 60 °C for 10 s, and 72 for 30 s. The primer sequences used for PCR were as follows 6 , 37 .\nPR - A  forward, 5′- GGTTTTGTTAGGGATAGGATTTTTT-3′;\nPR - A  reverse, 5′-ACTACCTCCAACACCCCTTATAACT-3′;\nPR - B  forward-1, 5′-TGTGGGTGGTATTTTTAATGAGA -3′;\nPR - B  reverse-1, 5′-CCCCCTCACTAAAACCCTAAA-3′;\nPR - B  forward-2, 5′-AGTATGGAGTTAGTAGAAGTT-3′;\nPR - B  reverse-2, 5′-TCACAAGTCCAACACTTAAATAACT-3′.\nPCR products were purified using AMPure beads (Beckman) and subjected to library construction using the NEBNext Ultra DNA Library Prep Kit for Illumina (New England BioLabs). Libraries were sequenced on an Illumina Miseq using Reagent Kit V2 (300 cycles)(Illumina) to generate 150 bp paired-end reads.\nTo generate immortalized human endometrial cells, normal endometrial cells obtained from a patient (41 years old) with cervical squamous cell carcinoma were cultivated in Advanced DMEM:F12 (Invitrogen) containing 100 ng/ml EGF (Sigma), 10 μM Y-27632 (Selleck Chemcals), 2% B-27 (Thermo Fisher Scientific), and 10 nM 17β-estradiol (Calbiochem). Lentiviral vectors expressing TERT, cyclin D1, and mutant CDK4 (CDK4 R24C : an inhibitor-resistant form of CDK4) were constructed by recombination with a lentiviral vector, CSII-CMV-RfA (a kind gift from Dr. Hiroyuki Miyoshi). To obtain infectious lentiviral particles, 293T cells (ATCC) were transfected with indicated constructs and packaging plasmids (pCAG-HIVgp and pCMV-VSV-G-RSV-Rev) (kind gifts from Dr Hiroyuki Miyoshi). For immortalization, the normal endometrial cells were transduced with mutant CDK4 (CDK4 R24C ), cyclin D1, and TERT via lentivirus-mediated gene transfer. The immortalized cells were seeded in the matrigel (Rensselaer)-coated six-well plates. Human embryonic kidney 293T cells (ATCC) were cultured in DMEM-F12 containing 10% fetal calf serum (Life Technologies). The 293T cells (5 × 10 6  cells) were plated in a 10 cm dish, incubated for 24 h, and then transfected with 1 μg of the retroviral plasmids (HA-tagged wild-type or mutant  KRAS  (G12C or G12D) (Addgene; catalog number 75282, 58901, and 58902) or  PIK3CA  (cloned cDNA subcloned into pBabe backbone vector) with ecotropic packaging plasmids (Takara Bio) for 24 h using Lipofectamine LTX (Thermo Fisher). After 24 h, the virus-containing medium was filtered (0.45 μm filter, Millipore) and supplemented with 4 μg/ml polybrene (Nacalai). For retroviral gene transductions, the culture medium was replaced by the appropriate retroviral supernatant (1:4 dilutions) and incubated at 37 °C. Transduced immortalized cells were cultured with DNG (Sigma) at 37 °C, followed by counting of cell numbers using a Countess II cell counter (Invitrogen). For cell cycle analyses, BrdU incorporation was performed using the APC-BrdU kit (BD Pharmingen) and measured by FACs Canto II (BD Biosciences).\nCells were lysed in 1% Triton X-100 lysis buffer (20 mM Tris-HCl at pH 8, 100 mM NaCl, 10% glycerol) for 30 min on ice. Cell lysates (20–100 μg) were subjected to 10% SDS-polyacrylamide gel electrophoresis and immunoblotting using anti-vinculin antibody (1:5000: clone SPM227; Abcam) or anti-HA tag antibody (1:1000; clone 6E2; Cell Signaling Technology). Secondary antibody used was horseradish peroxidase-conjugated anti-mouse immunoglobulin G (1:5000; NA931V; GE Healthcare).\nTotal RNA was extracted using the RNeasy Mini kit (Qiagen) and reverse-transcribed using the SuperScript IV VILO cDNA synthesis kit VI (Thermo Fisher). The resulting cDNAs were diluted to 1:5–10 and served as templates for real-time PCR using Power SYBR Green PCR Master Mix (Applied Biosystems) plus 250 nM forward primer and 250 nM reverse primer on an ABI 7700 instrument (Applied Biosystems). All procedures were performed according to the manufacturer’s instructions. The primer sequences used for real-time reverse transcriptase–PCR were as follows;  GAPDH  forward, 5′-GGAAGCTCACTGGCATGGCC-3′; reverse, 5′-CCTGCTTCACCACCTTCTTG-3′;  PR - A/B  forward, 5′-GAGCACTGGATGCTGTTGCT-3′; reverse, 5′-GGCTTAGGGCTTGGCTTTC-3′;  KRAS  forward, 5′-GCAAGAGTGCCTTGACGATAC-3′; reverse, 5′-TCCAAGAGACAGGTTTCTCCA-3′;  PIK3CA  forward, 5′-TCTGAACGTTTGTAAAGAAGC-3′; reverse, 5′-CATTATTTGGAGAAACTATTA-3′. Data were normalized to the housekeeping gene  GAPDH . Results were calculated using the comparative threshold cycle method (2-ΔΔ Ct ).\nStatistical analyses used for judging somatic mutations were described in the Methods section under the heading “Validation of single-nucleotide variations by TDS”. Statistical significance values shown in Figs.  5 b,  6 b–d, and  8  were determined using Welch’s  t -test. Comparisons of the distribution of categorical variables in different groups were performed using Fisher’s exact test (Table  1 ).\nFurther information on research design is available in the  Nature Research Reporting Summary  linked to this article.\n\nSupplementary Information \n Peer Review File \n Description of Additional Supplementary Files \n Supplementary Data 1 \n Supplementary Data 2 \n Supplementary Data 3 \n Supplementary Data 4 \n Supplementary Data 5 \n Supplementary Data 6 \n Supplementary Data 7 \n Supplementary Data 8 \n Supplementary Data 9 \n Supplementary Data 10 \n Supplementary Data 11 \n Supplementary Data 12 \n Supplementary Data 13 \n Supplementary Data 14 \n Supplementary Data 15 \n Supplementary Data 16 \n Supplementary Data 17 \n Supplementary Data 18 \n Supplementary Data 19 \n Supplementary Data 20 \n Supplementary Data 21 \n Supplementary Data 22 \n Supplementary Data 23 \n Supplementary Data 24 \n Supplementary Data 25 \n Supplementary Data 26 \n Supplementary Data 27 \n Supplementary Data 28 \n Supplementary Data 29 \n Reporting Summary\nSupplementary Information\nPeer Review File\nDescription of Additional Supplementary Files\nSupplementary Data 1\nSupplementary Data 2\nSupplementary Data 3\nSupplementary Data 4\nSupplementary Data 5\nSupplementary Data 6\nSupplementary Data 7\nSupplementary Data 8\nSupplementary Data 9\nSupplementary Data 10\nSupplementary Data 11\nSupplementary Data 12\nSupplementary Data 13\nSupplementary Data 14\nSupplementary Data 15\nSupplementary Data 16\nSupplementary Data 17\nSupplementary Data 18\nSupplementary Data 19\nSupplementary Data 20\nSupplementary Data 21\nSupplementary Data 22\nSupplementary Data 23\nSupplementary Data 24\nSupplementary Data 25\nSupplementary Data 26\nSupplementary Data 27\nSupplementary Data 28\nSupplementary Data 29\nReporting Summary","source_license":"CC0","license_restricted":false}