Rebecca Feldman

Update on EGFR Mutational Testing and the Potential of Noninvasive Liquid Biopsy in Non–Small-cell Lung Cancer

Abstract Mutations in the epidermal growth factor receptor (EGFR) are important drivers of non–small‐cell lung cancer (NSCLC) and have led to the emergence of EGFR‐targeted therapies as critical treatment options for NSCLC. Although these agents have shown clinical activity in NSCLC patients, acquired resistance to EGFR‐targeted agents is inevitable. Therefore, the ability to conveniently biopsy patient tumors is of increasing importance as new mechanisms of resistance and agents to target these resistance mutations are identified. Rapid and accurate EGFR mutational testing of patient biopsy specimens, including liquid biopsy specimens, allows for the identification of potentially actionable mutations that could guide treatment. In the present review, we discuss the various methods and best practices for tumor sampling and EGFR mutational testing in NSCLC.

Identification of molecular targets in vulvar cancers

OBJECTIVES To identify molecular alterations that contribute to vulvar cancer pathogenesis with the intent of identifying molecular targets for treatment. METHODS After retrospective analysis of a database of molecularly-profiled gynecologic cancer patients, 149 vulvar cancer patients were included and tested centrally at a CLIA laboratory (Caris Life Sciences, Phoenix, AZ). Tests included one or more of the following: gene sequencing (Sanger or next generation sequencing [NGS]), protein expression (immunohistochemistry [IHC]), and gene amplification (C/FISH). A Fishers exact test was used when indicated with a p-value≤0.05 indicating significance. RESULTS Median age was 65. 85% had squamous cell carcinoma (SCC) and 15% adenocarcinoma (ADC) histologies. 46% had metastatic (Stage IV) disease. Targeted hot-spot sequencing identified variants in the following genes: TP53 (33%), PIK3CA/BRCA2 (8%, 10%, respectively), HRAS/FBXW7 (5%, 4%, respectively) and ERBB4/GNAS (3%, 3% respectively). Mutations in AKT1, ATM, FGFR2, KRAS, NRAS (n=1, respectively) and BRAF (n=2) also occurred. Specific protein changes for targetable genes included clinically pathogenic mutations commonly found in other cancers (e.g. PIK3CA: exon 9 [E545K], RAS: G13D, Q61L, BRCA2: S1667X, BRAF: R443T, FBXW7: E471fs, etc.). Drug targets identified by IHC and ISH methodologies include cMET (32% IHC, 2% ISH), PDL1 (18%), PTEN loss (56%), HER2 (4% IHC, 2% ISH) and hormone receptors (AR, 4%; ER, 11%; PR, 4%). Comparisons between SCC and ADC identified differential rates for AR, ER, HER2 and GNAS with an increased presence in ADC (p-values all <0.05). CONCLUSIONS Molecularly-guided precision medicine could provide vulvar cancer patients alternative, targeted treatment options.

Abstract B18: PI3K/mTOR pathway aberrations across diverse solid tumors: Analysis of 13,500 patients

Background: Molecular aberrations in the phosphatidylinositol 3-kinase (PI3K) pathway have been documented across cancers, especially PIK3CA mutations and mutation or loss of PTEN. These alterations may be relevant to therapies targeting the PI3K/mTOR signaling pathway. Methods: Molecular profiling was performed on 13500 tumors (>30 cancer types) at a CLIA-certified laboratory (Caris Life Sciences). Tests included next generation sequencing (NGS), protein expression (immunohistochemistry), and gene amplification (FISH or CISH). Results: PIK3CA mutations across cancers were distributed at 43% in exon 9, 33% in exon 20, and 24% in exons 1, 2, 7 or 13. PIK3CA mutations by cancer type were distributed in exons 9 and 20 as follows: breast, 34%/47%; endometrial, 30%/34%; colorectal, 54%/25%; bladder 74%/14%. Frequency and type of co-incidence of biomarker aberrations in PIK3CA wildtype (WT) vs PIK3CA mutated (MT) patients and in PTEN WT vs. PTEN MT patients were collated across cancers. Aggregate differences in gene mutation rates (45 genes evaluated), protein expression rates (18 proteins), and copy number (5 biomarkers) were measured. The biomarkers with significantly different (p value≤0.05) percent mutations are listed for PIK3CA WT vs PIK3CA MT patients and for PTEN WT vs PTEN MT cases, respectively (2 were not significant, indicated with a #): TP53, 49% in PIK3CA WT vs 35% in PIK3CA MT; 47% in PTEN WT vs 34% in PTEN MT. BRAF, 3.8% vs 2.1%; 3.6% vs 4.1%#. KRAS, 16% vs 21%; 17% vs 19%#. FBXW7, 2% vs 6%; 2% vs 6%. FGFR2, 1% vs 3%; 1% vs 7%. ATM, 3% vs 4%; %3 vs 5%. CTNNB1, 2% vs 7%; 2% vs 12%. ERBB2, 1% vs 2%; 1% vs 2%. PTEN, 5% vs 16% (PIK3CA WT vs. MT) and PIK3CA, 12% vs 33% (PTEN WT vs. MT). The biomarkers with protein expression above threshold by IHC (unless noted) are also listed, for PIK3CA WT vs PIK3CA MT patients and for PTEN WT vs PTEN MT cases, respectively. PTEN loss, 29% vs 31%; 26% vs 73%. TOP2A, 73% vs 86%; 73% vs 84%. AR, 16% vs 29%; 18% vs 23%. ER, 23% vs 44%; 24% vs 49%. PR, 13% vs 33%; 4% vs 42%. MGMT, 58 vs 54%; 58% vs 42%. PGP, 17 vs 12%; 17% vs 10%. TS, 49 vs 52%; 49% vs 60%. Her2, 6 vs 11%; 7% vs 4%. Lineage-specific differences of note are described herein, and differences in frequency, specific mutation, gender association, and co-incidence of associated biomarkers by cancer type will be described. Breast, endometrial, bladder and colorectal cancers had the highest PIK3CA mutation rate (32%, n=1500; 36%, n=1060; 21%, n=166; 14%, n=1390, respectively), while endometrial, prostate and high grade glioma cancers had the highest PTEN mutation rate (35%, n=1060; 18%, n=110; 14%, n=360, respectively). PTEN loss for endometrial, colorectal and breast cancers was 49%, 47% and 33%, respectively. Co-mutation of PTEN and PIK3CA occurred in 1% of colorectal, 1.5% of breast, 0% of prostate, and 12% of endometrial cancers. Conclusions: Different patterns of biomarker alterations across cancers may provide new insights relevant to targeted therapy. For example, in the 31% of PIK3CA mutated patients who also have a PTEN loss (a proposed resistance mechanism in targeting the mTOR pathway), alternative and/or combination therapies might be recommended. The findings indicate the need to evaluate patient samples for patterns in biomarker expression and alterations, to better understand the molecular biology and to formulate a personalized therapy approach, which might include combination therapies, based on the patterns seen in each patient profiled. Citation Format: Zoran Gatalica, Sherri Z. Millis, Joanne Xiu, David Arguello, Rebecca Feldman, Razelle Kurzrock. PI3K/mTOR pathway aberrations across diverse solid tumors: Analysis of 13,500 patients. [abstract]. In: Proceedings of the AACR Special Conference: Targeting the PI3K-mTOR Network in Cancer; Sep 14-17, 2014; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(7 Suppl):Abstract nr B18.