Clinicogenomic landscape and function ofPIK3CA,AKT1, andPTENmutations in breast cancer

Clinicogenomic landscape and function of PIK3CA, AKT1, and PTEN mutations in breast cancer | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Clinicogenomic landscape and function of PIK3CA , AKT1 , and PTEN mutations in breast cancer View ORCID Profile Jacqueline J. Tao , View ORCID Profile Saumya D. Sisoudiya , View ORCID Profile Hanna Tukachinsky , View ORCID Profile Alexa Schrock , View ORCID Profile Smruthy Sivakumar , Ethan S. Sokol , View ORCID Profile Neil Vasan doi: https://doi.org/10.1101/2025.06.18.25329632 Jacqueline J. Tao 1 Columbia University Irving Medical Center , New York, NY MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Jacqueline J. Tao Saumya D. Sisoudiya 2 Foundation Medicine Inc. , Cambridge, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Saumya D. Sisoudiya Hanna Tukachinsky 2 Foundation Medicine Inc. , Cambridge, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Hanna Tukachinsky Alexa Schrock 2 Foundation Medicine Inc. , Cambridge, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Alexa Schrock Smruthy Sivakumar 2 Foundation Medicine Inc. , Cambridge, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Smruthy Sivakumar Ethan S. Sokol 2 Foundation Medicine Inc. , Cambridge, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Neil Vasan 3 Department of Medicine, New York University Grossman School of Medicine , New York, NY 4 Perlmutter Cancer Center, NYU Langone Health , New York, NY Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Neil Vasan For correspondence: neil.vasan{at}nyulangone.org Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Purpose To comprehensively characterize the clinical and genomic landscapes of PIK3CA, AKT1, and PTEN alterations and examine their functional implications in AKT-driven breast cancer. Experimental Design Comprehensive genomic profiling of 51,767 breast tumors was performed with FoundationOne ® CDx or FoundationOne ® . We examined the genomic landscape of PIK3CA , PTEN , and AKT1 alterations and their distribution across clinical variables of interest. Prior deep mutational scanning (DMS) data was used to functionally characterize clinical PTEN variants. Results There were 29,157 total variants across PIK3CA, AKT1, and PTEN , including pathogenic variants and VUS. The most frequently altered gene was PIK3CA (37.4% of cases), followed by PTEN (13.5%), then AKT1 (5.4%). The most common alterations in each gene were PIK3CA H1047R (35.6% of PIK3CA -altered cases), E545K (19.7%), and E542K (11.7%); AKT1 E17K (69.7%); and PTEN homozygous copy number deletion (37.3%). PIK3CA alterations were less prevalent in patients of African genetic ancestry (27.1% vs 38.6% in European genetic ancestry), while AKT1 and PTEN alterations were balanced across ancestries. PIK3CA , AKT1 , and PTEN pathogenic alterations were all mutually exclusive to each other. Using available DMS data on missense PTEN mutations, we found that 32.5% showed discordant effects on protein stability and phosphatase activity, underscoring the need for functional validation beyond predicted loss-of-function. Conclusions Here we present the landscape of PIK3CA , AKT1 , and PTEN alterations in the largest clinical cohort examined to date. The functional implications of lesser-known variants in each gene warrant further investigation by tools such as deep mutational scanning. Introduction The AKT pathway plays a critical role in multiple cellular functions including growth, proliferation, survival, and metabolism, and is one of the most frequently altered pathways across cancers. PIK3CA encodes the catalytic subunit of PI3Kα, which recruits and activates AKT and subsequent downstream signaling through mTORC1 1 . The lipid phosphatase PTEN metabolizes the lipid phosphoinositide species PIP 3 , antagonizing the effects of PI3K. Consequently, aberrant PI3K pathway activation primarily arises due to activating mutations in PIK3CA, along with activating mutations in AKT1 and inactivating alterations in PTEN 2 . The AKT pathway is altered in over 40% of estrogen receptor-positive (ER+) breast cancers 3 , and numerous agents targeting pathway constituents have been developed and approved over the last two decades. One of the first approved agents targeting this pathway was the mTOR inhibitor everolimus, which was shown in the BOLERO-2 trial to improve progression free survival (PFS) in combination with exemestane in patients with endocrine-resistant metastatic breast cancer (MBC) 4 . Subsequently, the PI3Kα-specific inhibitor alpelisib was approved for PIK3CA -mutated MBC based on the SOLAR-1 trial, where it doubled PFS in combination with fulvestrant 5 . More recently, the mutant-selective PI3Kα inhibitor inavolisib was developed and found to have synergistic activity with palbociclib plus fulvestrant for patients with advanced breast cancer relapsed within 12 months after completing adjuvant endocrine therapy 6 . However, several of these agents are associated with significant on-target toxicities including grade 3+ hyperglycemia in more than one-third of patients receiving alpelisib. Recently, the AKT inhibitor capivasertib was approved for patients with ER+ MBC with mutations in PIK3CA , AKT1 , and/or PTEN after progression on first-line endocrine-based therapy 7 . In the CAPItello-291 study, capivasertib combined with fulvestrant more than doubled PFS in patients with qualifying genomic alterations (median PFS 7.3 months versus 3.1 months with fulvestrant alone) 8 . Notably, clinical endpoints were not significantly improved in the wild-type population, highlighting the importance of PIK3CA / AKT1 / PTEN alterations as biomarkers of sensitivity to capivasertib. Capivasertib also demonstrated a favorable toxicity profile compared with older generations of PI3K inhibitors, including lower rates of hyperglycemia (2.3% grade 3-4 versus 36.6% grade 3-4 with alpelisib), accelerating its adoption in the clinical setting over older agents. Although significant progress has been made in characterizing the AKT pathway at the genomic level 9 , 10 , many prior dedicated studies of PIK3CA/AKT1/PTEN have had limited sequencing coverage, analyzed smaller genomic data sets, or examined restricted clinical subsets. An early landscape analysis of PIK3CA/AKT1/PTEN used mass spectroscopy-based sequencing to analyze 547 breast tumors 11 ; more recent examples have described this 3-gene landscape in 1,967 luminal type breast cancers that underwent gene panel sequencing 12 and 7,450 hormone receptor-positive breast cancers that underwent next generation sequencing 13 . With the recent FDA approval of capivasertib for patients with breast cancer harboring PIK3CA , AKT1 , or PTEN alterations, it is increasingly critical to understand the clinical landscape of these genomic subsets. We have previously leveraged large-scale genomic data sets to investigate the landscape of multi- PIK3CA mutated tumors, enabling unique insights into the genetic heterogeneity and tissue specificities of multi- PIK3CA mutations 14 . While PIK3CA mutations have been extensively studied, far less is known about the prevalence, co-alteration patterns, and clinical outcomes associated with AKT1 and PTEN alterations in breast cancer. Here we assess the frequencies, distributions, clinical associations, and co-occurrence patterns of PIK3CA, AKT1, and PTEN variants in the largest breast cancer dataset to date (n = 51,767) that integrates genomic and clinical data across all three alterations, offering a unique opportunity to define their distinct and overlapping roles in therapeutic response and resistance. Methods Comprehensive genomic profiling of a breast cancer cohort Comprehensive genomic profiling (CGP) of formalin-fixed, paraffin-embedded tissue sections was performed using the FoundationOne®CDx assay or the laboratory-developed test predecessor, FoundationOne®, as part of routine clinical care in a Clinical Laboratory Improvement Amendments-certified, College of American Pathologists-accredited laboratory (Foundation Medicine, Inc.). This study included 51,767 breast cancer samples profiled between August 2014 and September 2023. Approval for this study, including a waiver of informed consent and Health Insurance Portability and Accountability Act (HIPAA) waiver of authorization, was obtained from the Western Institutional Review Board (protocol no. 20152817). Genomic analysis CGP was performed on hybrid capture-selected libraries spanning exons of at least 300 cancer-related genes and select introns of genes frequently rearranged in cancer. Processing of the sequence data and identification of different classes of genomic alterations was carried out as previously described 15 , 16 . The alterations identified included single nucleotide variants (missense, nonsense, and splice site mutations), indels (in-frame and frameshift mutations), copy number alterations, and rearrangement events. Alterations were classified as either known or likely pathogenic using annotations from various sources, including their occurrence in the COSMIC database, previous scientific literature-based knowledge about the affected gene (such as truncations and deletions in known tumor suppressor genes), or mutations that have previously been characterized as pathogenic; all other uncharacterized alterations were classified as variants of unknown significance (VUS). Histopathologic and clinical characteristics HER2 status was determined from the HER2 ( ERBB2 ) amplification status based on the FoundationOne® or FoundationOne®CDx assays. ER status was derived from accompanying pathology reports, where available. Clinical data including biopsy site (local versus lymph node vs metastatic) were obtained from the submitted test requisition form. Genetic ancestry of each patient was predicted using a single nucleotide polymorphism (SNP)-based approach. Briefly, the profiled SNPs that overlapped with those captured in phase 3 of the 1000 Genomes Project were projected down to five principal components that were then used to train a random forest classifier to identify the following ancestry groups: European (EUR), African (AFR), East Asian (EAS), South Asian (SAS), and admixed American (AMR) 17 . Co-occurrence and mutual exclusivity analyses The dataset was interrogated for patterns of co-occurrence and mutual exclusivity of PIK3CA, AKT1, and PTEN mutations with other cancer-associated genes targeted as part of the assays. A Fisher’s exact test was used to identify significantly co-occurring (OR > 1) as well as mutually exclusive (OR < 1) patterns using a FDR-adjusted p-value threshold of 0.05. A Benjamini-Hochberg FDR correction was applied to adjust for multiple comparisons. Functional characterization of clinical PTEN alterations To explore the functional implications of the PTEN variants in this clinical cohort, we examined two published deep mutational scanning (DMS) data sets characterizing the effects of single amino acid substitutions on PTEN function. In Matreyek et al 2018 18 , abundance scores were determined by measuring the steady-state intracellular abundance of PTEN variants in cultured human cells using VAMP-seq (Variant Abundance by Massively Parallel Sequencing). Abundance scores were refined and generated for additional PTEN variants in Matreyek et al 2021 19 . Scores ranged from 0, reflecting total loss of abundance, to 1, reflecting wild type (WT)-like abundance. Based on the abundance score, each PTEN variant was assigned an abundance class of low, possibly low, possibly WT-like, or WT-like. In Mighell et al 2018 20 , fitness scores reflecting the lipid phosphatase activity of PTEN variants were determined by assessing enzymatic ability to reverse toxicity via PIP 3 dephosphorylation in a humanized yeast system. Variants were assigned functional categories based on fitness score percentiles: scores below the upper two-tailed 95 th percentile for nonsense variants ( < -2.13) were designated truncation-like, scores within the two-tailed 95 th percentile for synonymous variants (-1.11 to 0.89) were designated WT-like, and scores in between these ranges (-2.13 to -1.11) were designated hypomorphic. Here we extracted abundance and fitness scores corresponding to the PTEN missense and nonsense variants in our clinical cohort and assigned functional classifications for each variant based on these scores. Functional designations created in the original publications were consolidated into binary categories of pathogenic (abundance classes of low and possibly low; fitness score categories of truncation-like and hypomorphic) and non-pathogenic (abundance classes of WT-like and possibly WT-like; fitness score categories of WT-like and >WT). For each missense PTEN variant, functional classifications derived from the abundance score and fitness score were compared. Statistical analyses Categorical variables were compared between groups using the Fisher’s exact test, with an FDR correction for multiple testing. A p-value ≤0.05 was considered statistically significant. Statistics, computation, and plotting were carried out using R 3.6.1 (R Foundation for Statistical Computing). Data availability All relevant data are provided within the article and its accompanying Supplementary Data. Due to HIPAA requirements, we are not authorized to share individualized patient genomic data, which contains potentially identifying or sensitive patient information. Foundation Medicine is committed to collaborative data analysis, with well-established and widely utilized mechanisms by which investigators can query our core genomic database of >700,000 de-identified sequenced cancers to obtain aggregated datasets. For more information and mechanisms of access, please contact the corresponding author(s) or the Foundation Medicine, Inc. Data Governance Council at data.governance.council{at}foundationmedicine.com . Results Baseline cohort characteristics This analysis included 51,767 breast cancer tumor samples. The majority (51,199; 99%) of the cohort were female and median age was 59 years (IQR 50-68 years). HER2 amplification was assessed in all samples, of which 4312 (8.3%) were HER2+. ER status was available in 4219 cases, of which 2409 (57.1% of assessable cases) were ER+/HER2- and 1408 (33.4%) were ER-/HER2-. The most common ancestries represented were European (72%) and African (14%). Tumor samples were obtained from a metastatic site (47%), local site (33%), or lymph node (12%), with the remaining samples having unknown or ambiguous biopsy site information (8%). Prevalence and spectrum of AKT pathway alterations There were 29,157 total variants in PIK3CA, AKT1, and PTEN identified in the cohort. The most frequently altered PI3K-pathway gene was PIK3CA (37.4% of samples; 19,384/51,767), followed by PTEN (13.5%; 6,991/51,767) then AKT1 (5.4%; 2,782/51,767), including both pathogenic alterations and VUS in all genes. When taking only pathogenic alterations into account, PIK3CA was altered in 36.5% of all samples, PTEN in 12.7%, and AKT1 in 4.7%. Among 1,024 distinct PIK3CA alterations identified, the most common variant type was missense mutations (690/1,024; 67.4% of all PIK3CA variants) followed by in-frame mutations (252; 24.6%; Figure 1 , Supplementary Table S1). The most common mutations were H1047R (35.6% of PIK3CA -altered cases), E545K (19.7%), and E542K (11.7%), consistent with the known mutational hotspots 21 . The fourth most common PIK3CA alteration was amplification (6.1%). Among 288 distinct AKT1 alterations identified, missense mutations remained the most common variant type (205/288; 71.2% of all AKT1 variants), with the most common mutation being E17K (69.7% of AKT1 -altered cases; Figure 1 , Supplementary Table S2). The second most common AKT1 alteration was gene amplification (14.0%). Finally, among 1,723 distinct PTEN alterations identified, the most common variant types were frameshift mutations (721/1,723; 41.9% of PTEN variants), missense mutations (494; 28.7%), and splice site mutations (246; 14.3%). The most common individual PTEN alteration was gene deletion (37.3% of PTEN -altered cases; Figure 1 , Supplementary Table S3). Download figure Open in new tab Figure 1. Frequency, distribution, and coding type of PIK3CA , AKT1 , and PTEN variants. The most frequently altered PI3K-pathway gene was PIK3CA (37.4% of patients), followed by PTEN (13.5%) then AKT1 (5.4%). A) Lollipop plots of PIK3CA , AKT1 , and PTEN mutations. B) Prevalence of individual variants in each gene. The most common variants in each gene were PIK3CA H1047R (35.6% of PIK3CA -altered cases), AKT1 E17K (69.7%), and PTEN deletion (37.3%). C) Distribution of variant coding types in each gene. The most common variant coding types were PIK3CA missense mutation (67.4%), AKT1 missense mutation (71.2%), and PTEN frameshift mutation (41.9%). Multiple pathogenic PIK3CA alterations were seen in 3,148 samples (16.2% of all PIK3CA -altered samples and 6.1% of overall cohort). Pathogenic alterations in more than one gene were most commonly seen with PIK3CA and PTEN (2018 samples, 4% of cohort) followed by PIK3CA and AKT1 (322 samples, 0.6%) then AKT1 and PTEN (71 samples, 0.14%). Clinical and demographic associations We next examined the distribution of PIK3CA, AKT1, and PTEN mutations stratified by clinical variables including receptor subtype ( Figures 2A and 2D , Supplementary Table S4), patient ancestry ( Figures 2B and 2E , Supplementary Table S5), and biopsy site ( Figures 2C and 2F , Supplementary Table S6). PIK3CA pathogenic variants were more prevalent in ER+/HER2- and HER2+ disease (40.3%, p =6.0x10 -36 and 37.6% of cases, p =2.3x10 -32 ) than in ER-/HER2- disease (20.9%), consistent with prior reports 11 , 22 . However, variants outside the 542, 545, and 1047 codons were more common in ER-/HER2- (42%) than ER+/HER2- or HER2+ cases (33%, p =0.002 and 33%, p =0.002). AKT1 mutations were most prevalent in ER+/HER2- disease (6.0%) and less common in HER2+ or ER-/HER2- disease (1.7%, p =4.7x10 -20 and 3.0%, p =3.5x10 - 5 ). In contrast, PTEN alterations were more commonly found in ER-/HER2- (17.9%) than in ER+/HER2- and HER2+ disease (11.3%, p =1.8x10 -8 and 3.9%, p =2x10 -57 ). Download figure Open in new tab Figure 2. Prevalence of gene variants by breast cancer receptor subtype, genetic ancestry, and biopsy site. A) PIK3CA variants were enriched in ER+/HER2- and HER2+ disease (altered in 40.3% and 37.6% of cases, respectively) and AKT1 variants were enriched in ER+/HER2-disease (6.0%). In contrast, PTEN variants were most prevalent in ER-/HER2- disease (17.9%). B-C) PIK3CA alterations were less prevalent in patients with African ancestry (27.1% vs 38.6% in European ancestry) and enriched in metastases (39.6% vs 33.2% in local tumors). D) PIK3CA variants outside the 542, 545, and 1047 codons were more common in ER-/HER2- disease (42%) compared to ER+/HER2- or HER2+ disease (33% and 33%). E, F) PIK3CA variants by ancestry and biopsy site. PIK3CA pathogenic alterations were less prevalent in patients with African ancestry than other groups, both in the full cohort (27.1% vs 38.6% in Europeans, p =9.6x10 -81 ) and in the ER+/HER2- disease subset (31.2% vs 41.1% in Europeans, p =0.002). Additionally, among ER+/HER2- cases only, patients with South Asian ancestry had a higher prevalence of PIK3CA pathogenic alterations than other groups (68.9% vs 41.1% in Europeans, p =0.002). PIK3CA pathogenic variants were enriched in metastases compared to local tumors (39.6% vs 33.2%, p =6x10 -41 ). The distribution of individual PIK3CA variants was similar across ancestries and biopsy sites. The prevalence of pathogenic AKT1 and PTEN alterations was similar across all ancestries and biopsy sites. Co-occurrence and mutual exclusivity analyses Next, we characterized the patterns of co-occurrence and mutual exclusivity between pathogenic variants in PIK3CA, AKT1, and PTEN and other sequenced genes ( Figure 3 ; Supplementary Tables S7-S9). Regarding PI3K pathway genes, PIK3CA , AKT1 , and PTEN pathogenic alterations were all strongly mutually exclusive with each other ( PIK3CA/AKT1 odds ratio [OR] 0.25, p <10 -60 ; PIK3CA/PTEN OR 0.74, p =6.6x10 -25 ; AKT1/PTEN OR 0.20, p <10 -60 ), suggesting that a single driver mutation may be sufficient for aberrant pathway activation. Notably, the degree of mutual exclusivity was lowest between PIK3CA and PTEN , corresponding to the higher rates of co-mutations observed in these two genes compared to the other combinations. Download figure Open in new tab Figure 3. Co-occurrence and mutual exclusivity analyses of pathogenic variants in PIK3CA , AKT1 , and PTEN . Pathogenic variants in these 3 genes were all mutually exclusive to each other. Notable co-occurrences included PIK3CA with SOX2, PRKCI, MAP3K1, TERC, CDH1, and TBX3 ; AKT1 with NF1 and CDH1 ; and PTEN with FAS , TP53 , and RB1 . Notable mutual exclusivities include PIK3CA with TP53, BRCA1/2, and STK11 ; AKT1 with ERBB2 and MYC; and PTEN with ERBB2, GATA3, and ESR1. Y-axis is capped at p-value of 10E-60. PIK3CA was significantly co-altered with several other cancer-associated genes including SOX2, PRKCI, MAP3K1, TERC, CDH1, and TBX3 . Interestingly the strongest association was with SOX2 , a relationship that has not previously been described in the breast cancer literature, though there are reports suggesting a role of PIK3CA and SOX2 co-amplification in the pathogenesis of head and neck cancers 23 . Several other significantly co-occurring genes have well-known associations with PIK3CA including CDH1 and TBX3 , whose losses are hallmarks of invasive lobular carcinoma (ILC) 24 , 25 , and MAP3K1 , which is associated with luminal A phenotype 26 – 28 . These findings are consistent with the enrichment of ILC and luminal A breast cancers for PIK3CA mutations. Several tumor suppressors were mutually exclusive with PIK3CA including TP53, BRCA1/2, and STK11 . Other notable mutual exclusivities included PIK3R1, FGF23, CCND2, MYC, KDM5A, and GATA3 . AKT1 was significantly co-altered with NF1 and CDH1 , an association which has been previously described in ILC 29 . There were several shared co-occurrence patterns with PIK3CA , including MAP3K1 , which may reflect the increased prevalence of both PIK3CA and AKT1 in ER+/HER2- tumors . AKT1 was mutually exclusive with ERBB2 and MYC . PTEN was significantly co-altered with FAS (also located on 10q23) as well as the tumor suppressors TP53 and RB1 . PTEN is known to be an essential mediator of Fas-mediated apoptosis, and PTEN loss can lead to impaired apoptosis and increased cell survival 30 . Combined PTEN and TP53 loss is known to be associated with poor therapeutic response and poor prognosis, particularly in triple negative breast cancers 31 , 32 . Notable mutually exclusivities with PTEN included ERBB2, GATA3, and ESR1 . Co-occurrence analyses were also performed on VUS in the three genes of interest, which showed weakly significant results (Supplementary Figure S1; Supplementary Tables S7-S9). Functional characterization of clinical PTEN alterations Among the more than 1,700 clinical PTEN variants identified in our cohort, a notable proportion are variants of uncertain significance with unclear functional implications. We leveraged large-scale experimental data sets previously generated in cell models to explore the functions of clinical PTEN variants in our cohort. Specifically, we examined two published deep mutational scanning (DMS) data sets characterizing the effects of single amino acid substitutions on PTEN abundance (protein expression) or function (effects on lipid phosphatase activity as measured by PIP 3 levels) 18 – 20 . The original published data sets generated abundance scores for 4,547 missense or nonsense PTEN variants and fitness scores for 6,904 missense or nonsense PTEN variants. Our clinical cohort included 610 single amino acid substitution PTEN variants (494 missense and 116 nonsense). Of these, 339 (55.6% of all PTEN variants) had an available abundance score and 536 (87.9%) had an available fitness score; 298 (48.9%) variants had both abundance and fitness scores available. Abundance and fitness scores for each missense and nonsense PTEN variant in our clinical cohort are collated (Supplementary Table S10). As expected, nonsense variants exhibited statistically significantly lower abundance and fitness scores compared to missense variants ( p =1.12x10 - 28 and p =4.93x10 -25 for abundance and fitness scores, respectively; Figure 4A ). Nearly all nonsense variants with available DMS data were appropriately classified as pathogenic by both abundance score (n = 49/49; 100%) and fitness score (n = 88/92; 95.7%). However, there was significant variation in the functional classifications assigned to individual missense variants. By abundance score, 148 (51.0% of missense variants with available abundance score) were pathogenic and 142 (49.0%) were non-pathogenic; by fitness score, 231 (52.0% of missense variants with available fitness score) were pathogenic and 213 (48.0%) were non-pathogenic. For missense variants with both abundance and fitness scores available (n = 261), we compared the functional classifications assigned by each assay ( Figures 4B and 4C ). Notably, 31.8% (83/261) of missense variants were classified as non-pathogenic by both assays, highlighting a substantial proportion of missense PTEN variants that do not contribute to pathogenicity. Meanwhile, 35.6% (93/298) were concordantly classified as pathogenic by both assays. The remaining one-third of missense variants had discordances in functional classification (85, 32.5%), exhibiting either loss of abundance without loss of phosphatase activity (39, 14.9%) or loss of phosphatase activity without loss of abundance (46, 17.6%). These discordances likely reflect the distinct phenotypic effects of mutations at different amino acid residues. Download figure Open in new tab Figure 4. Deep mutational scanning data for missense and nonsense PTEN variants. A) Distribution of abundance and fitness scores among missense versus nonsense variants in the cohort, from Matreyek et al 2021 and Mighell et al 2018. Mean abundance and fitness scores for nonsense variants are significantly lower than for missense variants (mean scores for each group are represented by dashed lines; p =1.12x10 -28 and p =4.93x10 - 25 , respectively). B) Set diagrams depicting degree of concordance in functional classification by abundance versus fitness score, for missense variants only. C) Scatterplot of abundance and fitness scores for missense variants only, colored by concordance in functional classification between the two assays. Discussion Here we report the largest landscape study of PIK3CA , AKT1, and PTEN genomic alterations in breast tumors to date, encompassing 29,157 alterations across the three genes. The frequency and distribution of PIK3CA and AKT1 alterations in this cohort was consistent with prior reports 11 – 13 , 22 , 33 . Interestingly, the frequency of PTEN alterations was higher (13.5%) than in prior reports of PTEN alterations in breast cancer ( < 10%) 12 , 13 , which could be attributable to the detection of additional PTEN variants compared to prior studies which used targeted sequencing of certain exons. The most common PIK3CA variants we observed were H1047R, E545K, E542K, N345K, and H1047L, consistent with previous reports 34 , 35 . While hotspot mutations in PIK3CA are well-established as predictors of response to AKT pathway inhibitors, the roles of non-hotspot mutations are variably understood. A subset of these rare variants were included in the companion diagnostic used in the SOLAR-1 trial 5 , 35 , while others including the fourth most common mutation in our data set (N345K) 36 , 37 have been associated with alpelisib sensitivity in preclinical studies. We found that 16.2% of PIK3CA -altered samples had multiple PIK3CA alterations, similar to previous reporting 38 , which have been shown to result in increased PI3K activity and increased sensitivity to PI3Kα inhibitors. AKT1 E17K accounted for over two-thirds of variants in the gene, leaving a notable minority of non-hotspot alterations whose biological and clinical implications remain to be clarified. One study found that a subset of non-E17K missense mutations in the long tail of AKT1 and AKT2 led to increased PI3K signaling and sensitized tumors to AKT inhibition; additionally, a group of in-frame duplications led to distinct structural changes, AKT activation, and hypersensitivity to ATP-competitive but not allosteric AKT inhibitors 39 . Further clarification of mutant-specific effects on pathway activity and mutant-specific therapeutic vulnerabilities represent an important outstanding area of investigation. We found that ER-/HER2- cases had a higher proportion of non-hotspot PIK3CA variants than other receptor subtypes. However, given negative results from several prior trials of PI3K pathway inhibition in ER-/HER2- breast cancer 40 – 43 , it remains to be clarified whether hotspot and/or non-hotspot PIK3CA variants predict for PI3K/AKT inhibitor response in triple negative disease. Our demographic analyses revealed that PIK3CA alterations were less common in patients with African ancestry than other groups, among all receptor subtypes and in ER+/HER2- disease alone, which has been demonstrated in smaller prior studies 44 – 47 . Here we additionally found no difference in the prevalence of AKT1 and PTEN variants across ancestries, suggesting that ancestry-based differences in PIK3CA prevalence are gene-specific rather than affecting the PI3K pathway globally. This could be due to differential tumor biology and mechanisms that may limit in African American patients the acquisition of PIK3CA mutations which are early clonal events, and highlight one biological explanation for lower representation of African American patients in PIK3CA biomarker-based targeted therapy trials. We also found that PIK3CA prevalence was significantly higher in patients with South Asian ancestry and ER+/HER2-disease, underscoring the need for representative patient enrollment in biomarker-based clinical trials. Our gene association analyses corroborated prior findings that PIK3CA , AKT1 , and PTEN pathogenic alterations are strongly mutually exclusive with each other 11 , 28 , 35 , likely reflecting redundancies in PI3K pathway activation between these genes. Several significant co-occurrences involving PIK3CA and AKT1 were consistent with the literature and with their prevalence in certain histopathologic subtypes. These included previously recognized associations with MAPK1 and CDH1/NF1 , which are known to be enriched in ER+ disease and ILC, respectively. MAPK1 loss-of-function variants occurring in PIK3CA -mutated cell lines have also been shown to result in resistance to PI3Kα inhibitors and AKT inhibitors 27 , suggesting their potential value as a predictive biomarker for AKT pathway inhibitor resistance. We identified a novel co-occurrence tendency between PIK3CA and SOX2 , a combination which has been implicated in the pathogenesis of head and neck cancers but is not well-described in breast cancers. PIK3CA and AKT1 tended to be mutually exclusive with tumor suppressors such as MYC , while PTEN -altered samples were enriched for mutations in other tumor suppressors such as FAS and TP53 , a combination which is recognized as a poor prognostic factor especially in triple negative disease. The functional characterization of PTEN VUS remains a challenge in clinical genomics, as accurate classification can directly impact patient management. Our analysis highlights the value of large-scale experimental datasets, such as DMS, in resolving the pathogenicity of these variants. Notably, we identified a substantial proportion of missense PTEN variants (31.8%) that were consistently classified as non-pathogenic by both abundance and fitness-based assays, underscoring the importance of functional data in refining variant interpretation and potentially reducing the burden of uncertainty in clinical decision-making. However, discordances in nearly one-third of missense variants suggest that a substantial proportion of mutations may not predict straightforward loss of function and therefore warrant further mechanistic investigation in the laboratory as to if they predict for AKT inhibitor sensitivity. Expanding and refining such datasets will be critical for improving precision in molecular diagnostics and therapeutic guidance. Our study has limitations including the lack of available ER status on a substantial subset of patients, which may limit the interpretation of the related analyses, though the mutational distributions that we observed across receptor subtypes were consistent with prior reports. Samples are restricted to patients residing in the United States, which could limit the generalizability of the ancestry-related findings. In conclusion, we have leveraged a large CGP dataset of >51,000 breast tumors to generate insights on the clinicogenomic landscape of an important biomarker triad in breast cancer. We identify a wide spectrum of alterations in PIK3CA/AKT1/PTEN encompassing well-established pathogenic variants as well as rare variants with unknown clinical significance. The prevalence of non-hotspot mutations, some of which are known to mediate sensitivity to older PI3K inhibitors, supports the use of CGP over smaller gene panels for identifying potentially actionable variants. Importantly, further preclinical and clinical studies are needed to clarify the roles of lesser-known variants as predictive biomarkers for the expanding collection of PI3K pathway inhibitors. Ancestry-based differences in PIK3CA prevalence are significant and should be taken into consideration in clinical studies of PI3K inhibition. As shown here, DMS data sets can be leveraged to generate insights into the functional implications of rare clinical variants. Data Availability All relevant data are provided within the article and its accompanying Supplementary Data. Download figure Open in new tab Supplementary Figure S1. Co-occurrence and mutual exclusivity analyses of all variants (pathogenic + VUS; top) and VUS only (bottom) in PIK3CA , AKT1 , and PTEN . Y-axis is capped at p-value of 10E-60. Footnotes Conflict of interest statement: S.D.S, H.T., A.S., S.S., and E.S.S. are employees of Foundation Medicine and have equity interest in Roche. N.V. is a consultant for Apertor Therapeutics, Avenzo Therapeutics, and Scorpion Therapeutics; has equity with Heligenics, Inc. and Meliora Therapeutics; and is on the scientific advisory board of Meliora Therapeutics. Funding: This study was supported by NIH K08CA245192, the Breast Cancer Alliance Young Investigator Grant, Gilead Science Research Scholars Grant, and a Conquer Cancer Foundation Young Investigator Award 2025. References 1. ↵ Vasan N , Cantley LC . At a crossroads: how to translate the roles of PI3K in oncogenic and metabolic signalling into improvements in cancer therapy . Nat Rev Clin Oncol 2022 ; 19 ( 7 ): 471 – 485 . DOI: 10.1038/s41571-022-00633-1 . OpenUrl CrossRef 2. ↵ Vanhaesebroeck B , Perry MWD , Brown JR , Andre F , Okkenhaug K . PI3K inhibitors are finally coming of age . Nat Rev Drug Discov 2021 ; 20 ( 10 ): 741 – 769 . DOI: 10.1038/s41573-021-00209-1 . OpenUrl CrossRef PubMed 3. ↵ Castel P , Toska E , Engelman JA , Scaltriti M . The present and future of PI3K inhibitors for cancer therapy . Nat Cancer 2021 ; 2 ( 6 ): 587 – 597 . DOI: 10.1038/s43018-021-00218-4 . OpenUrl CrossRef PubMed 4. ↵ Baselga J , Campone M , Piccart M , et al. Everolimus in postmenopausal hormone-receptor-positive advanced breast cancer . N Engl J Med 2012 ; 366 ( 6 ): 520 – 9 . DOI: 10.1056/NEJMoa1109653 . OpenUrl CrossRef PubMed Web of Science 5. ↵ Andre F , Ciruelos E , Rubovszky G , et al. Alpelisib for PIK3CA-Mutated, Hormone Receptor-Positive Advanced Breast Cancer . N Engl J Med 2019 ; 380 ( 20 ): 1929 – 1940 . DOI: 10.1056/NEJMoa1813904 . OpenUrl CrossRef PubMed 6. ↵ Turner NC , Im SA , Saura C , et al. Inavolisib-Based Therapy in PIK3CA-Mutated Advanced Breast Cancer . N Engl J Med 2024 ; 391 ( 17 ): 1584 – 1596 . DOI: 10.1056/NEJMoa2404625 . OpenUrl CrossRef PubMed 7. ↵ FDA approves capivasertib with fulvestrant for breast cancer. U.S. Food & Drug Administration . Nov 16, 2023 . ( https://www.fda.gov/drugs/resources-information-approved-drugs/fda-approves-capivasertib-fulvestrant-breast-cancer ). 8. ↵ Turner NC , Oliveira M , Howell SJ , et al. Capivasertib in Hormone Receptor-Positive Advanced Breast Cancer . N Engl J Med 2023 ; 388 ( 22 ): 2058 – 2070 . DOI: 10.1056/NEJMoa2214131 . OpenUrl CrossRef PubMed 9. ↵ Millis SZ , Ikeda S , Reddy S , Gatalica Z , Kurzrock R . Landscape of Phosphatidylinositol-3-Kinase Pathway Alterations Across 19D784 Diverse Solid Tumors . JAMA Oncol 2016 ; 2 ( 12 ): 1565 – 1573 . DOI: 10.1001/jamaoncol.2016.0891 . OpenUrl CrossRef PubMed 10. ↵ Razavi P , Chang MT , Xu G , et al. The Genomic Landscape of Endocrine-Resistant Advanced Breast Cancers . Cancer Cell 2018 ; 34 ( 3 ): 427 – 438 e6. DOI: 10.1016/j.ccell.2018.08.008 . OpenUrl CrossRef PubMed 11. ↵ Stemke-Hale K , Gonzalez-Angulo AM , Lluch A , et al. An integrative genomic and proteomic analysis of PIK3CA, PTEN, and AKT mutations in breast cancer . Cancer Res 2008 ; 68 ( 15 ): 6084 – 91 . DOI: 10.1158/0008-5472.CAN-07-6854 . OpenUrl Abstract / FREE Full Text 12. ↵ Tada H , Miyashita M , Harada-Shoji N , et al. Clinicopathogenomic analysis of PI3K/AKT/PTEN-altered luminal metastatic breast cancer in Japan . Breast Cancer 2024 . DOI: 10.1007/s12282-024-01639-6 . OpenUrl CrossRef 13. ↵ Bhave MA , Quintanilha JCF , Tukachinsky H , et al. Comprehensive genomic profiling of ESR1, PIK3CA, AKT1, and PTEN in HR(+)HER2(-) metastatic breast cancer: prevalence along treatment course and predictive value for endocrine therapy resistance in real-world practice . Breast Cancer Res Treat 2024 ; 207 ( 3 ): 599 – 609 . DOI: 10.1007/s10549-024-07376-w . OpenUrl CrossRef PubMed 14. ↵ Sivakumar S , Jin DX , Rathod R , et al. Genetic Heterogeneity and Tissue-specific Patterns of Tumors with Multiple PIK3CA Mutations . Clin Cancer Res 2023 ; 29 ( 6 ): 1125 – 1136 . DOI: 10.1158/1078-0432.CCR-22-2270 . OpenUrl CrossRef PubMed 15. ↵ Frampton GM , Fichtenholtz A , Otto GA , et al. Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing . Nat Biotechnol 2013 ; 31 ( 11 ): 1023 – 31 . DOI: 10.1038/nbt.2696 . OpenUrl CrossRef PubMed 16. ↵ Milbury CA , Creeden J , Yip WK , et al. Clinical and analytical validation of FoundationOne(R)CDx, a comprehensive genomic profiling assay for solid tumors . PLoS One 2022 ; 17 ( 3 ): e0264138 . DOI: 10.1371/journal.pone.0264138 . OpenUrl CrossRef PubMed 17. ↵ Jiagge E , Jin DX , Newberg JY , et al. Tumor sequencing of African ancestry reveals differences in clinically relevant alterations across common cancers . Cancer Cell 2023 ; 41 ( 11 ): 1963 – 1971 e3. DOI: 10.1016/j.ccell.2023.10.003 . OpenUrl CrossRef PubMed 18. ↵ Matreyek KA , Starita LM , Stephany JJ , et al. Multiplex assessment of protein variant abundance by massively parallel sequencing . Nat Genet 2018 ; 50 ( 6 ): 874 – 882 . DOI: 10.1038/s41588-018-0122-z . OpenUrl CrossRef PubMed 19. ↵ Matreyek KA , Stephany JJ , Ahler E , Fowler DM . Integrating thousands of PTEN variant activity and abundance measurements reveals variant subgroups and new dominant negatives in cancers . Genome Med 2021 ; 13 ( 1 ): 165 . DOI: 10.1186/s13073-021-00984-x . OpenUrl CrossRef PubMed 20. ↵ Mighell TL , Evans-Dutson S , O’Roak BJ . A Saturation Mutagenesis Approach to Understanding PTEN Lipid Phosphatase Activity and Genotype-Phenotype Relationships . Am J Hum Genet 2018 ; 102 ( 5 ): 943 – 955 . DOI: 10.1016/j.ajhg.2018.03.018 . OpenUrl CrossRef PubMed 21. ↵ Samuels Y , Wang Z , Bardelli A , et al. High frequency of mutations of the PIK3CA gene in human cancers . Science 2004 ; 304 ( 5670 ): 554 . DOI: 10.1126/science.1096502 . OpenUrl FREE Full Text 22. ↵ Xiao W , Zhang G , Chen B , et al. Mutational Landscape of PI3K-AKT-mTOR Pathway in Breast Cancer: Implications for Targeted Therapeutics . J Cancer 2021 ; 12 ( 14 ): 4408 – 4417 . DOI: 10.7150/jca.52993 . OpenUrl CrossRef PubMed 23. ↵ Montoro-Jimenez I , Granda-Diaz R , Menendez ST , et al. Combined PIK3CA and SOX2 Gene Amplification Predicts Laryngeal Cancer Risk beyond Histopathological Grading . Int J Mol Sci 2024 ; 25 ( 5 ). DOI: 10.3390/ijms25052695 . OpenUrl CrossRef 24. ↵ An Y , Adams JR , Hollern DP , et al. Cdh1 and Pik3ca Mutations Cooperate to Induce Immune-Related Invasive Lobular Carcinoma of the Breast . Cell Rep 2018 ; 25 ( 3 ): 702 – 714 e6. DOI: 10.1016/j.celrep.2018.09.056 . OpenUrl CrossRef PubMed 25. ↵ Ciriello G , Gatza ML , Beck AH , et al. Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer . Cell 2015 ; 163 ( 2 ): 506 – 19 . DOI: 10.1016/j.cell.2015.09.033 . OpenUrl CrossRef PubMed 26. ↵ Nixon MJ , Formisano L , Mayer IA , et al. PIK3CA and MAP3K1 alterations imply luminal A status and are associated with clinical benefit from pan-PI3K inhibitor buparlisib and letrozole in ER+ metastatic breast cancer . NPJ Breast Cancer 2019 ; 5 : 31 . DOI: 10.1038/s41523-019-0126-6 . OpenUrl CrossRef PubMed 27. ↵ Avivar-Valderas A , McEwen R , Taheri-Ghahfarokhi A , et al. Functional significance of co-occurring mutations in PIK3CA and MAP3K1 in breast cancer . Oncotarget 2018 ; 9 ( 30 ): 21444 – 21458 . DOI: 10.18632/oncotarget.25118 . OpenUrl CrossRef PubMed 28. ↵ Mosele F , Stefanovska B , Lusque A , et al. Outcome and molecular landscape of patients with PIK3CA-mutated metastatic breast cancer . Ann Oncol 2020 ; 31 ( 3 ): 377 – 386 . DOI: 10.1016/j.annonc.2019.11.006 . OpenUrl CrossRef PubMed 29. ↵ Sokol ES , Feng YX , Jin DX , et al. Loss of function of NF1 is a mechanism of acquired resistance to endocrine therapy in lobular breast cancer . Ann Oncol 2019 ; 30 ( 1 ): 115 – 123 . DOI: 10.1093/annonc/mdy497 . OpenUrl CrossRef PubMed 30. ↵ Di Cristofano A , Kotsi P , Peng YF , Cordon-Cardo C , Elkon KB , Pandolfi PP . Impaired Fas response and autoimmunity in Pten+/- mice . Science 1999 ; 285 (5436): 2122 – 5 . DOI: 10.1126/science.285.5436.2122 . OpenUrl Abstract / FREE Full Text 31. ↵ Liu JC , Voisin V , Wang S , et al. Combined deletion of Pten and p53 in mammary epithelium accelerates triple-negative breast cancer with dependency on eEF2K . EMBO Mol Med 2014 ; 6 ( 12 ): 1542 – 60 . DOI: 10.15252/emmm.201404402 . OpenUrl Abstract / FREE Full Text 32. ↵ Gasparyan M , Lo MC , Jiang H , Lin CC , Sun D . Combined p53- and PTEN-deficiency activates expression of mesenchyme homeobox 1 (MEOX1) required for growth of triple-negative breast cancer . J Biol Chem 2020 ; 295 ( 34 ): 12188 – 12202 . DOI: 10.1074/jbc.RA119.010710 . OpenUrl Abstract / FREE Full Text 33. ↵ Rudolph M , Anzeneder T , Schulz A , et al. AKT1 (E17K) mutation profiling in breast cancer: prevalence, concurrent oncogenic alterations, and blood-based detection . BMC Cancer 2016 ; 16 : 622 . DOI: 10.1186/s12885-016-2626-1 . OpenUrl CrossRef PubMed 34. ↵ Martinez-Saez O , Chic N , Pascual T , et al. Frequency and spectrum of PIK3CA somatic mutations in breast cancer . Breast Cancer Res 2020 ; 22 ( 1 ): 45 . DOI: 10.1186/s13058-020-01284-9 . OpenUrl CrossRef PubMed 35. ↵ Rugo HS , Raskina K , Schrock AB , et al. Biology and Targetability of the Extended Spectrum of PIK3CA Mutations Detected in Breast Carcinoma . Clin Cancer Res 2023 ; 29 ( 6 ): 1056 – 1067 . DOI: 10.1158/1078-0432.CCR-22-2115 . OpenUrl CrossRef PubMed 36. ↵ Gymnopoulos M , Elsliger MA , Vogt PK . Rare cancer-specific mutations in PIK3CA show gain of function . Proc Natl Acad Sci U S A 2007 ; 104 ( 13 ): 5569 – 74 . DOI: 10.1073/pnas.0701005104 . OpenUrl Abstract / FREE Full Text 37. ↵ Dogruluk T , Tsang YH , Espitia M , et al. Identification of Variant-Specific Functions of PIK3CA by Rapid Phenotyping of Rare Mutations . Cancer Res 2015 ; 75 ( 24 ): 5341 – 54 . DOI: 10.1158/0008-5472.CAN-15-1654 . OpenUrl Abstract / FREE Full Text 38. ↵ Vasan N , Razavi P , Johnson JL , et al. Double PIK3CA mutations in cis increase oncogenicity and sensitivity to PI3Kalpha inhibitors . Science 2019 ; 366 (6466): 714 – 723 . DOI: 10.1126/science.aaw9032 . OpenUrl Abstract / FREE Full Text 39. ↵ Shrestha Bhattarai T , Shamu T , Gorelick AN , et al. AKT mutant allele-specific activation dictates pharmacologic sensitivities . Nat Commun 2022 ; 13 ( 1 ): 2111 . DOI: 10.1038/s41467-022-29638-1 . OpenUrl CrossRef PubMed 40. ↵ Pascual J , Turner NC . Targeting the PI3-kinase pathway in triple-negative breast cancer . Ann Oncol 2019 ; 30 ( 7 ): 1051 – 1060 . DOI: 10.1093/annonc/mdz133 . OpenUrl CrossRef 41. Martin M , Chan A , Dirix L , et al. A randomized adaptive phase II/III study of buparlisib, a pan-class I PI3K inhibitor, combined with paclitaxel for the treatment of HER2-advanced breast cancer (BELLE-4) . Ann Oncol 2017 ; 28 ( 2 ): 313 – 320 . DOI: 10.1093/annonc/mdw562 . OpenUrl CrossRef PubMed 42. Dent RA , Kim SB , Oliveira M , et al. Ipatasertib plus Paclitaxel for Patients with PIK3CA/AKT1/PTEN-Altered Locally Advanced Unresectable or Metastatic Triple-Negative Breast Cancer in the IPATunity130 Phase III Trial . Clin Cancer Res 2024 ; 30 ( 19 ): 4329 – 4338 . DOI: 10.1158/1078-0432.CCR-24-0465 . OpenUrl CrossRef PubMed 43. ↵ Update on the CAPItello-290 Phase III trial for Truqap plus chemotherapy in advanced or metastatic triple-negative breast cancer. AstraZeneca . June 18, 2024 . ( https://www.astrazeneca.com/media-centre/press-releases/2024/update-on-capitello-290-phase-iii-trial.html ). 44. ↵ Chen JW , Murugesan K , Newberg JY , et al. Comparison of PIK3CA Mutation Prevalence in Breast Cancer Across Predicted Ancestry Populations . JCO Precis Oncol 2022 ; 6 : e2200341 . DOI: 10.1200/PO.22.00341 . OpenUrl CrossRef 45. Pitt JJ , Riester M , Zheng Y , et al. Characterization of Nigerian breast cancer reveals prevalent homologous recombination deficiency and aggressive molecular features . Nat Commun 2018 ; 9 ( 1 ): 4181 . DOI: 10.1038/s41467-018-06616-0 . OpenUrl CrossRef PubMed 46. Jouali F , Marchoudi N , Talbi S , et al. Detection of PIK3/AKT pathway in Moroccan population with triple negative breast cancer . BMC Cancer 2018 ; 18 ( 1 ): 900 . DOI: 10.1186/s12885-018-4811-x . OpenUrl CrossRef PubMed 47. ↵ Omilian AR , Wei L , Hong CC , et al. Somatic mutations of triple-negative breast cancer: a comparison between Black and White women . Breast Cancer Res Treat 2020 ; 182 ( 2 ): 503 – 509 . DOI: 10.1007/s10549-020-05693-4 . OpenUrl CrossRef PubMed View the discussion thread. 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