<div>Abstract<p>PI3Kα inhibitors have shown clinical activity in PIK3CA-mutated estrogen receptor-positive (ER<sup>+</sup>) patients with breast cancer. Using whole genome CRISPR/Cas9 sgRNA knockout screens, we identified and validated several negative regulators of mTORC1 whose loss confers resistance to PI3Kα inhibition. Among the top candidates were TSC1, TSC2, TBC1D7, AKT1S1, STK11, MARK2, PDE7A, DEPDC5, NPRL2, NPRL3, C12orf66, SZT2, and ITFG2. Loss of these genes invariably results in sustained mTOR signaling under pharmacologic inhibition of the PI3K–AKT pathway. Moreover, resistance could be prevented or overcome by mTOR inhibition, confirming the causative role of sustained mTOR activity in limiting the sensitivity to PI3Kα inhibition. Cumulatively, genomic alterations affecting these genes are identified in about 15% of <i>PIK3CA</i>-mutated breast tumors and appear to be mutually exclusive. This study improves our understanding of the role of mTOR signaling restoration in leading to resistance to PI3Kα inhibition and proposes therapeutic strategies to prevent or revert this resistance.</p>Significance:<p>These findings show that genetic lesions of multiple negative regulators of mTORC1 could limit the efficacy of PI3Kα inhibitors in breast cancer, which may guide patient selection strategies for future clinical trials.</p></div>
Abstract Adenomyoepithelioma (AME) is a rare biphasic proliferative breast lesion, which may resemble salivary gland epithelial-myoepithelial carcinomas (EMCs). Most AMEs have an indolent clinical course, but malignant transformation and local and distant recurrences have been reported. We sought to define the mutational landscape of AMEs and investigate the functional impact of recurrent likely pathogenic mutations identified in these tumors. Nineteen AMEs were subjected to whole-exome massively parallel sequencing (MPS, n=7) or targeted capture MPS using MSK-IMPACT assay (n=12). Somatic genetic alterations and the cancer cell fraction of mutations were defined using state-of-the-art bioinformatics algorithms. Selected genes (i.e. HRAS and PIK3CA) were subjected to Sanger sequencing in a series of 17 additional AMEs (total n=36). Non-tumorigenic mammary epithelial cells (i.e. MCF10A, MCF10A with the PIK3CAH1047R mutation and MCF12A), which are estrogen receptor (ER)-negative, were utilized for 2D and 3D functional studies. Of 36 cases, 22 were ER-positive and 14 were ER-negative. MPS analysis revealed a low mutation burden and HRASQ61 and PIK3CA hotspot mutations in 6/19 (32%) and 11/19 (58%) AMEs, respectively. All HRASQ61 and all but one PIK3CA mutations were clonal. ER-positive and ER-negative AMEs were fundamentally histologically and genetically distinct. Whilst ER-positive AMEs displayed recurrent PIK3CA mutations (50%, 11/22) but lacked HRAS mutations, ER-negative AMEs displayed, in addition to PIK3CA mutations (57%, 8/14), recurrent HRASQ61 mutations (57%, 8/14). HRASQ61 mutations co-occurred with PIK3CA mutations (50%, 4/8), PIK3R1 deletions (12.5%, 1/8) and/or CDKN2A homozygous deletions (25%, 2/8). HRASQ61 mutations, but not PIK3CA mutations, were significantly associated with ER-negativity (100% vs 21%), concurrent carcinoma (50% vs 7%), axillary metastases (38% vs 0%), high proliferation (63% vs 4%), necrosis (63% vs 11%) and nuclear pleomorphism (75% vs 29%). In vitro forced HRASQ61R expression in MCF10A and MCF12A cells resulted in increased proliferation and transformation. In 3D organotypic cell cultures, forced HRASQ61R resulted in a highly disorganized growth pattern, a partial loss of epithelial phenotype and acquisition of aberrant myoepithelial differentiation, which was more overt in PIK3CA-mutant MCF10A cells. In conclusion, AMEs are phenotypically and genetically heterogeneous. Whilst PIK3CA hotspot mutations occur across the spectrum of lesions, HRASQ61 hotspot mutations are restricted to ER-negative AMEs, which should arguably be classified as breast EMCs. Our genomic and functional analyses are consistent with the notion that HRASQ61 mutations are driver events in the pathogenesis of ER-negative AMEs and may be sufficient for the acquisition of myoepithelial differentiation in breast cells. Citation Format: Felipe C. Geyer, Kathleen A. Burke, Anqi Li, Anastasios D. Papanastatiou, Fresia Pareja, Anne S. Schulteis, Charlotte K. Ng, Salvatore Piscuoglio, Marcia Edelweiss, Luciano G. Martelotto, Pier Selenica, Maria R. Filippo, Gabriel S. Macedo, Achim Jungbluth, Hannah Y. Wen, Juan Palazzo, Zsuzsanna Varga, Emad Rakha, Ian O. Ellis, Brian Rubin, Britta Weigelt, Jorge S. Reis-Filho. Massively parallel sequencing analysis of breast adenomyoepitheliomas reveals the heterogeneity of the disease and identifies a subset driven by HRAS hotspot mutations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3379. doi:10.1158/1538-7445.AM2017-3379
Lobular carcinoma in situ (LCIS) is a preinvasive lesion of the breast. We sought to define its genomic landscape, whether intralesion genetic heterogeneity is present in LCIS, and the clonal relatedness between LCIS and invasive breast cancers.Experimental Design: We reanalyzed whole-exome sequencing (WES) data and performed a targeted amplicon sequencing validation of mutations identified in 43 LCIS and 27 synchronous more clinically advanced lesions from 24 patients [9 ductal carcinomas in situ (DCIS), 13 invasive lobular carcinomas (ILC), and 5 invasive ductal carcinomas (IDC)]. Somatic genetic alterations, mutational signatures, clonal composition, and phylogenetic trees were defined using validated computational methods.WES of 43 LCIS lesions revealed a genomic profile similar to that previously reported for ILCs, with CDH1 mutations present in 81% of the lesions. Forty-two percent (18/43) of LCIS were found to be clonally related to synchronous DCIS and/or ILCs, with clonal evolutionary patterns indicative of clonal selection and/or parallel/branched progression. Intralesion genetic heterogeneity was higher among LCIS clonally related to DCIS/ILC than in those nonclonally related to DCIS/ILC. A shift from aging to APOBEC-related mutational processes was observed in the progression from LCIS to DCIS and/or ILC in a subset of cases.Our findings support the contention that LCIS has a repertoire of somatic genetic alterations similar to that of ILCs, and likely constitutes a nonobligate precursor of breast cancer. Intralesion genetic heterogeneity is observed in LCIS and should be considered in studies aiming to develop biomarkers of progression from LCIS to more advanced lesions.
Since the approval of pembrolizumab for advanced or recurrent PD-L1 positive (CPS > 1%) cervical cancer, the clinical characteristics associated with response have remained undefined. We sought to characterize the clinicopathologic features of patients with advanced cervical cancer at our institution who derived durable clinical benefit from treatment with pembrolizumab.We conducted a retrospective cohort study of 14 patients with recurrent or metastatic cervical cancer who received pembrolizumab monotherapy from August 2017 to November 2019 and were followed until November 1, 2020. Reviewed clinical data included age, histology, tumor molecular profiling results, stage at diagnosis, treatment history, baseline pattern of metastatic disease at initiation of anti-PD-1 therapy, and outcomes. Treatment response was evaluated by computed tomography using RECIST v1.1 criteria.The objective response rate was 21% (n = 3), including two partial responses and one complete response. Two patients (14%) had stable disease of six months or greater, for an observed durable clinical benefit rate of 36%. When stratified by those who derived clinical benefit, metastatic spread to lung and/or lymph node only at baseline was associated with improved response to pembrolizumab (n = 7, p = 0.02) and associated with significantly improved PFS and OS. Tumor mutational burden was higher in those with durable clinical benefit compared to non-responders (median 12.7 vs. 3.5 mutations/megabase, p = 0.03).Our findings highlight clinical features that may select for a population most likely to benefit from pembrolizumab monotherapy and underscores the need for identification of additional biomarkers of response.
Abstract Background: Forkhead box A1 (FOXA1) is a pioneer transcription factor (TF) for chromatin binding and function of other lineage-specific TFs essential for the normal development of endoderm-derived organs. Aberrant FOXA1 signaling, due to genetic amplification or mutations and/or overexpression, has been frequently detected in metastatic tumors of the breast, prostate, pancreas, bladder and thyroid, suggesting a general role and mechanism of FOXA1-driven tumorigenesis and disease progression. We recently reported that high levels of FOXA1 (H-FOXA1) promote endocrine-resistant (EndoR) and metastatic phenotypes in estrogen receptor (ER)+ breast cancer (BC) cells. Here we sought to uncover the role and the mechanisms by which H-FOXA1 promotes EndoR metastatic BC. Methods: Genomic sequencing data from an ER+/HER2- metastatic BC cohort (n=781, MSK-IMPACT; cBioportal) were used to compare mutations and copy number alterations of FOXA1 and ESR1. Genome-wide FOXA1-chromatin binding (cistrome) and distribution of the enhancer marks histone H3 lysine 27 acetylation (H3K27ac) and lysine 4 mono-methylation (H3K4me1) were analyzed by ChIP-seq in MCF7 cell model with inducible H-FOXA1. FOXA1 cistrome, H3K27ac distribution, and transcriptome of a FOXA1-overexpressing pancreatic ductal adenocarcinoma cell model (PDA-hT2) were obtained from NCBI GEO (GSE99311). The core regulatory circuitry (CRC) Mapper was used to identify auto-regulatory loop of TFs induced by H-FOXA1. Gene Ontology was used for gene set functional annotation. FOXA1-associated enhancers of ER+ metastatic vs. primary tumors were analyzed using the H3K27ac epigenome data (European Nucleotide Archive, PRJEB22757). Results: The FOXA1 and ESR1 genetic amplification and mutations displayed a largely mutually exclusive pattern in ER+/HER2- metastatic BC, suggesting a role of hyperactive FOXA1 signaling in promoting EndoR and metastatic BC distinct from that of the ESR1 mutations. FOXA1 overexpression in BC cells resulted in increased FOXA1 DNA binding and the establishment of more regions with gained H3K27ac and/or H3K4me1, suggesting a more accessible and active chromatin state. H-FOXA1-induced upregulated genes were enriched for the gained H3K27ac or H3K4me1, especially for the enhancers with both marks. An enhancer signature with gained and overlapped H3K27ac and H3K4me1 predicts genes enriched for proliferation, anti-apoptosis and developmental signaling. Upregulated genes induced by H-FOXA1 with gained enhancers were further enriched for pro-metastatic processes, sharing the same characteristics of cellular morphogenesis during embryonic development. Similar results were obtained using integrated data from the PDA-hT2 cell model, sharing enriched pro-metastatic genes predicted by the H-FOXA1-induced enhancer signature. A CRC auto-regulatory TF loop, comprising components of the AP-1 and SMAD families, was predicted to amplify the impact of this enhancer signature on activation of the pro-metastatic transcriptional programs. In line with our preclinical findings, epigenetic changes of active enhancers in ER+ metastatic vs. primary BC were associated with the H-FOXA1-induced enhancer signature. Conclusions: Our study suggests that in ER+ metastatic BC, genetic alterations of FOXA1 leading to hyperactive FOXA1 signaling involves epigenetic evolution to promote a pro-metastatic enhancer signature. This genome-wide H-FOXA1-induced enhancer signature supports the role of H-FOXA1 in unleashing oncogenic activities of lineage-specific TFs in many types of metastatic tumors. Developing therapeutics targeting FOXA1 itself or key components of the H-FOXA1-induced CRC is warranted to treat or prevent EndoR and metastatic BC effectively via targeting the entire aberrant transcriptional programs. Citation Format: Xiaoyong Fu, Resel Pereira, Carmine De Angelis, Sarmistha Nanda, Lanfang Qin, Jamunarani Veeraraghavan, Pier Selenica, Britta Weigelt, Jorge S Reis-Filho, Agostina Nardone, Rinath Jeselsohn, Myles Brown, Mothaffar F Rimawi, C Kent Osborne, Rachel Schiff. Identification of a high FOXA1-induced pro-metastatic enhancer signature in endocrine-resistant and metastatic breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD7-01.
Abstract For patients with hormone receptor-positive, early breast cancer without HER2 amplification, multigene expression assays including Oncotype DX ® recurrence score (RS) have been clinically validated to identify patients who stand to derive added benefit from adjuvant cytotoxic chemotherapy. However, cost and turnaround time have limited its global adoption despite recommendation by practice guidelines. We investigated if routinely available hematoxylin and eosin (H&E)-stained pathology slides could act as a surrogate triaging data substrate by predicting RS using machine learning methods. We trained and validated a multimodal transformer model, Orpheus, using 6,203 patients across three independent cohorts, taking both H&E images and their corresponding synoptic text reports as input. We showed accurate inference of recurrence score from whole-slide images (r = 0.63 (95% C.I. 0.58 - 0.68); n = 1,029), the raw text of their corresponding reports (r = 0.58 (95% C.I. 0.51 - 0.64); n = 972), and their combination (r = 0.68 (95% C.I. 0.64 - 0.73); n = 964) as measured by Pearson’s correlation. To predict high-risk disease (RS>25), our model achieved an area under the receiver operating characteristic curve (AUROC) of 0.89 (95% C.I. 0.83 - 0.94), and area under the precision recall curve (AUPRC) of 0.64 (95% C.I. 0.60 - 0.82), compared to 0.49 (95% C.I. 0.36 - 0.64) for an existing nomogram based on clinical and pathologic features. Moreover, our model generalizes well to external international cohorts, effectively identifying recurrence risk (r = 0.61, p < 10 -4 , n = 452; r = 0.60, p < 10 -4 , n = 575) and high-risk status (AUROC = 0.80, p < 10 -4 , AUPRC = 0.68, p < 10 -4 , n = 452; AUROC = 0.83, p < 10 -4 , AUPRC = 0.73, p < 10 -4 , n = 575) from whole-slide images. Probing the biologic underpinnings of the model decisions uncovered tumor cell size heterogeneity, immune cell infiltration, a proliferative transcription program, and stromal fraction as correlates of higher-risk predictions. We conclude that at an operating point of 94.4% precision and 33.3% recall, this model could help increase global adoption and shorten lag between resection and adjuvant therapy.
Low-grade serous carcinomas (LGSCs) and their precursors serous borderline tumours (SBTs) characteristically harbour mutations in BRAF, KRAS or NRAS but rarely in TP53, whereas high-grade serous carcinomas (HGSCs) are characterised by frequent TP53 mutations but rare BRAF, KRAS or NRAS mutations. In a small subset of cases, LGSCs and/or SBTs develop into high-grade tumours, including HGSCs and poorly differentiated carcinomas (PDCs). Here, we sought to define the repertoire of somatic genetic alterations in low-grade serous tumours and synchronous or metachronous high-grade adnexal carcinomas.
'/%3e%3c/defs%3e%3cpath fill='%23012169' d='M0 0h10080v5040H0z'/%3e%3cpath stroke='%23fff' stroke-width='.6' d='m0 0 6 3m0-3L0 3' clip-path='url(%23b)' transform='scale(840)'/%3e%3cpath stroke='%23e4002b' stroke-width='.4' d='m0 0 6 3m0-3L0 3' clip-path='url(%23c)' transform='scale(840)'/%3e%3cpath stroke='%23fff' stroke-width='840' d='M2520 0v2520M0 1260h5040'/%3e%3cpath stroke='%23e4002b' stroke-width='504' d='M2520 0v2520M0 1260h5040'/%3e%3cg fill='%23fff'%3e%3cuse xlink:href='%23d' x='2520' y='3780'/%3e%3cuse xlink:href='%23a' x='7560' y='4200'/%3e%3cuse xlink:href='%23a' x='6300' y='2205'/%3e%3cuse xlink:href='%23a' x='7560' y='840'/%3e%3cuse xlink:href='%23a' x='8680' y='1869'/%3e%3cuse xlink:href='%23e' x='8064' y='2730'/%3e%3c/g%3e%3c/svg%3e)