Conley, Barbara A.

Abstract Background. —Under the auspices of the College of American Pathologists, the current state of knowledge regarding pathologic prognostic factors (factors linked to outcome) and predictive factors (factors predicting response to therapy) in colorectal carcinoma was evaluated. A multidisciplinary group of clinical (including the disciplines of medical oncology, surgical oncology, and radiation oncology), pathologic, and statistical experts in colorectal cancer reviewed all relevant medical literature and stratified the reported prognostic factors into categories that reflected the strength of the published evidence demonstrating their prognostic value. Accordingly, the following categories of prognostic factors were defined. Category I includes factors definitively proven to be of prognostic import based on evidence from multiple statistically robust published trials and generally used in patient management. Category IIA includes factors extensively studied biologically and/or clinically and repeatedly shown to have prognostic value for outcome and/or predictive value for therapy that is of sufficient import to be included in the pathology report but that remains to be validated in statistically robust studies. Category IIB includes factors shown to be promising in multiple studies but lacking sufficient data for inclusion in category I or IIA. Category III includes factors not yet sufficiently studied to determine their prognostic value. Category IV includes factors well studied and shown to have no prognostic significance. Materials and Methods. —The medical literature was critically reviewed, and the analysis revealed specific points of variability in approach that prevented direct comparisons among published studies and compromised the quality of the collective data. Categories of variability recognized included the following: (1) methods of analysis, (2) interpretation of findings, (3) reporting of data, and (4) statistical evaluation. Additional points of variability within these categories were defined from the collective experience of the group. Reasons for the assignment of an individual prognostic factor to category I, II, III, or IV (categories defined by the level of scientific validation) were outlined with reference to the specific types of variability associated with the supportive data. For each factor and category of variability related to that factor, detailed recommendations for improvement were made. The recommendations were based on the following aims: (1) to increase the uniformity and completeness of pathologic evaluation of tumor specimens, (2) to enhance the quality of the data needed for definitive evaluation of the prognostic value of individual prognostic factors, and (3) ultimately, to improve patient care. Results and Conclusions. —Factors that were determined to merit inclusion in category I were as follows: the local extent of tumor assessed pathologically (the pT category of the TNM staging system of the American Joint Committee on Cancer and the Union Internationale Contre le Cancer [AJCC/UICC]); regional lymph node metastasis (the pN category of the TNM staging system); blood or lymphatic vessel invasion; residual tumor following surgery with curative intent (the R classification of the AJCC/UICC staging system), especially as it relates to positive surgical margins; and preoperative elevation of carcinoembryonic antigen elevation (a factor established by laboratory medicine methods rather than anatomic pathology). Factors in category IIA included the following: tumor grade, radial margin status (for resection specimens with nonperitonealized surfaces), and residual tumor in the resection specimen following neoadjuvant therapy (the ypTNM category of the TNM staging system of the AJCC/UICC). Factors in category IIB included the following: histologic type, histologic features associated with microsatellite instability (MSI) (ie, host lymphoid response to tumor and medullary or mucinous histologic type), high degree of MSI (MSI-H), loss of heterozygosity at 18q ( DCC gene allelic loss), and tumor border configuration (infiltrating vs pushing border). Factors grouped in category III included the following: DNA content, all other molecular markers except loss of heterozygosity 18q/DCC and MSI-H, perineural invasion, microvessel density, tumor cell–associated proteins or carbohydrates, peritumoral fibrosis, peritumoral inflammatory response, focal neuroendocrine differentiation, nuclear organizing regions, and proliferation indices. Category IV factors included tumor size and gross tumor configuration. This report records findings and recommendations of the consensus conference group, organized according to structural guidelines defined herein.

PURPOSE NCI-MATCH is a nationwide, histology-agnostic, signal-finding, molecular profile–driven trial for patients with refractory cancers, lymphomas, or myelomas. Patients with tumors harboring actionable aberration(s) in fibroblast growth factor receptor ( FGFR) 1-3 were treated with AZD4547, an oral FGFR1-3 inhibitor. METHODS Patients’ tumors were screened by next-generation sequencing for predefined FGFR amplification, activating mutations, or fusions. Patients were treated with AZD4547, 80 mg orally twice daily until progression of disease or drug intolerance. A response rate of 16% was considered promising. RESULTS Between July 2016 and June 2017, 70 patients were assigned and 48 received protocol therapy and are eligible for analysis. Patients’ tumors harbored FGFR1 or FGFR2 amplification (n = 20), FGFR2 or FGFR3 single-nucleotide variants (n = 19), or FGFR1 or FGFR3 fusions (n = 9). The most common primary tumors were breast (33.3%), urothelial (12.5%), and cervical cancer (10.4%).Grade 3 adverse events were consistent with those described in previous clinical trials. Confirmed partial responses were seen in 8% (90% CI, 3% to 18%) and were observed only in patients whose tumors harbored FGFR1-3 point mutations or fusions. Stable disease was observed in 37.5% (90% CI, 25.8% to 50.4%). The median progression-free survival (PFS) was 3.4 months, and the 6-month PFS rate was 15% (90% CI, 8% to 31%). For patients with tumors harboring FGFR fusions, the response rate was 22% (90% CI, 4.1% to 55%), and 6-month PFS rate was 56% (90% CI, 31% to 100%). CONCLUSION Preliminary signals of activity appeared to be limited to cancers harboring FGFR activating mutations and fusions, although AZD4547 did not meet the primary end point. Different FGFR somatic alterations may confer different levels of signaling potency and/or oncogene dependence.

5020 Background: V+C was well tolerated in a phase I trial and responses and prolonged disease stabilization were observed in BRCA + patients (pts).To assess the relative contribution of the PARP inhibitor to the efficacy observed for the combination, we conducted a randomized multicenter trial comparing the response rate (RR) of V and C to the RR of C alone in patients with deleterious BRCA mutations and recurrent ovarian, or primary peritoneal, fallopian tube or high-grade serous ovarian cancer. Methods: Pts were ≥ 18 yrs, KPS ≥ 70%, had adequate organ function, prior therapy with PARP inhibitors was allowed.Both drugs were administered orally qd; C 50 mg, V 60 mg; 21 day cycles. Pts were randomized to receive either C alone or V+C. At disease progression, pts on C alone were allowed to cross over to the combination. Radiologic imaging was performed at baseline and q 3 cycles for assessment of response. Dose reduction of V was allowed to 40 mg for gr 3 non-hematologic or gr 4 hematologic toxicities. The study design had an 88% power to detect the difference between a 15% RR for C alone versus 35% for V+C, early closure if fewer responses were observed on the combination arm in the first 65 pts enrolled (half of the total projected accrual). Results: Total of 74 pts were enrolled (36 pts C, 38 pts V+C), median age 58 (37-79 yrs), # of prior therapies: median 4 (1-9), 2 pts had prior PARP therapy. Treatment was well tolerated, Gr ≥ 2 toxicities per arm for initial regimen (# of pts): C alone: lymphopenia (2), mucositis (1); V+C: lymphopenia (4), anemia (2), leucopenia (2), neutropenia (2). Of the 74 pts evaluable for response at the interim analysis, 3 PRs observed in 36 pts on V+C and 5 PRs of 38 pts on C alone arm; thus accrual was stopped. PAR levels assessed by validated ELISA were inhibited (>80%) in PBMCs in 9/10 pts 4 hours post V, no inhibition with C alone. Conclusions: Addition of V, a PARP inhibitor, to C did not improve RR versus C alone. Exomic sequencing, gene expression studies, and Fanconi Anemia triple stain immunofluorescence (FATSI) assay for FancD2 nuclear foci formation using archival tissue are ongoing.

Abstract Background The proportion of tumors of various histologies that may respond to drugs targeted to molecular alterations is unknown. NCI-MATCH, a collaboration between ECOG-ACRIN Cancer Research Group and the National Cancer Institute, was initiated to find efficacy signals by matching patients with refractory malignancies to treatment targeted to potential tumor molecular drivers regardless of cancer histology. Methods Trial development required assumptions about molecular target prevalence, accrual rates, treatment eligibility, and enrollment rates as well as consideration of logistical requirements. Central tumor profiling was performed with an investigational next-generation DNA–targeted sequencing assay of alterations in 143 genes, and protein expression of protein expression of phosphatase and tensin homolog, mutL homolog 1, mutS homolog 2, and RB transcriptional corepressor 1. Treatments were allocated with a validated computational platform (MATCHBOX). A preplanned interim analysis evaluated assumptions and feasibility in this novel trial. Results At interim analysis, accrual was robust, tumor biopsies were safe (<1% severe events), and profiling success was 87.3%. Actionable molecular alteration frequency met expectations, but assignment and enrollment lagged due to histology exclusions and mismatch of resources to demand. To address this lag, we revised estimates of mutation frequencies, increased screening sample size, added treatments, and improved assay throughput and efficiency (93.9% completion and 14-day turnaround). Conclusions The experiences in the design and implementation of the NCI-MATCH trial suggest that profiling from fresh tumor biopsies and assigning treatment can be performed efficiently in a large national network trial. The success of such trials necessitates a broad screening approach and many treatment options easily accessible to patients.

Abstract Oncology has undergone major changes in systemic treatment options, from chemotherapy to antiangiogenic agents to tyrosine-kinase inhibitors to immunotherapy. Historically, a therapeutic agent is tested in separate trials as monotherapy or combined with investigational or approved agents/modalities, to determine antitumor activity in each histology based on the premise that each histology responds differently to the same treatment. This paradigm is time consuming and may or may not make use of molecular characterization to test each agent in each histology. However, with the expansion of biologic understanding and development of various biomarkers, e.g., estrogen receptor and Her 2 amplification, we move beyond the basic paradigm of general histology to one in which treatment is based upon molecular characteristics of the tumor. Examples of recent discoveries from this more modern paradigm are (1) multiple histologies sharing a common molecular profile and (2) a subset within a single histology having a given molecular characteristic. Various agents have been tested singularly in terms of molecular aberrations and histology, e.g., ALK inhibitors and NSCLC. However, with the rapid increase in the number of targeted agents in development, more facile and efficient clinical trial designs are needed. The National Cancer Institute (NCI) and ECOG-ACRIN Cancer Research Group (ECOG-ACRIN) collaborated in designing the Molecular Analysis for Therapy Choice trial (NCI-MATCH or EAY131), the first large-scale signal-finding precision medicine oncology trial in the United States to incorporate centralized NGS testing to direct patients to parallel (nonrandomized) phase II treatment arms under a master protocol. The trial is being conducted by the NCI National Clinical Trials Network (NCTN), with ECOG-ACRIN leading the trial. More than 100 investigators from across the NCTN adult cancer-oriented member groups (Alliance for Clinical Trials in Oncology, ECOG-ACRIN, NRG Oncology, and SWOG) have worked collaboratively to design and lead what is currently 30 treatment arms (subprotocols), with more arms in development. Wide-scale NCTN investigator involvement ensures use of the latest knowledge to define the actionable mutations required for eligibility and to make evidence-based selections of experimental agents. In NCI-MATCH, patients are assigned treatment based on the genomic alterations found in their tumors through genomic sequencing and other tests at the time of initial enrollment for screening. Unlike other phase II trials, each arm is open to advanced solid tumors, lymphomas, or myeloma that share a set of molecular aberrations, not restricted to a single histology. This strategy accommodates and encourages enrollment of rare tumors for which there are often no standard treatments and limited clinical trial options. NCI-MATCH has 10-30 concurrent treatment arms available to patients at any given time, testing both investigational agents and FDA-approved drugs for new indications. Most treatment arms have an enrollment goal of 35 patients, with some arms that address tumor gene variants of higher prevalence expanded to 70 patients. Together, the NCTN and NCI Community Oncology Research Program provide infrastructure for many clinical sites (>1100) to participate, providing ready access to physicians and patients; screening enrollment has occurred in all 50 states in the U.S, the District of Columbia, and Puerto Rico. A specific assay was developed for the trial (the MATCH assay), and a laboratory network was organized to rapidly process the tissue and efficiently interrogate for mutations. NCI and ECOG-ACRIN statisticians developed the analysis plan and are currently maintaining data that are closely monitored by safety experts for any adverse event signals. Lastly, a bioinformatics system (MATCHbox) was developed to coordinate molecular data collection and support rule-based decision-making based on those data. Because genomics in oncology is rapidly expanding and evolving, NCI-MATCH required flexibility to accommodate brisker screening accrual than anticipated, and adaptation to constantly emerging information about new drugs and new molecular alterations. The goal to sequence the tumors of 6,000 patients with NCI funding was achieved two years ahead of schedule, but that cohort was not sufficient to fill all the arms—in particular, those aimed at the most rarely occurring tumor gene aberrations. Currently, the goal for the trial is to complete the open treatment arms by allowing for designated commercial and academic laboratories to notify ordering physicians when genomic tests they ordered to guide clinical care indicate a potential eligibility to a NCI-MATCH arm with a rare variant and allow for enrollment to the relevant treatment subprotocol if the patient meets all subprotocol eligibility criteria. The tissue confirmation of the molecular abnormality on the MATCH assay by the central laboratories will be accomplished after subprotocol enrollment so that patient treatment will not be delayed for confirmation. A demonstration project is now under way to test the applicability of this approach and potentially develop common standards for future use. With tumor sequencing becoming a more and more common practice in oncology, this may allow patients with mutations of low prevalence to have investigational treatment options. NCI-MATCH is expanding its panel and definition of actionable mutations to allow greater flexibility to incorporate in real time new mutations supported with adequate levels of evidence. The valuable genomic and clinical outcome data collected in the trial will permit evaluation of efficacy of targeting certain actionable mutations with a specific agent. In addition, biospecimens are being collected to build a rich resource for conducting auxiliary biology studies that may answer questions about prevalence of mutations in the metastatic setting, prevalence of mutations in rare histologies, and resistance mechanisms of various targeted therapy. At this meeting, two abstracts will provide an overall trial update and present information about the prevalence of mismatch repair deficiency (dMMR) in the centrally screened population. Citation Format: Alice P. Chen, Peter J. O'Dwyer, Lyndsay Harris, Barbara A. Conley, Stanley R. Hamilton, Mickey Williams, Robert J. Gray, Shuli Li, Lisa M. McShane, Lawrence V. Rubinstein, Susanna I. Lee, Shaji Kumar, Edith P. Mitchell, James A. Zwiebel, Constantine A. Gatsonis, Lalitha K. Shankar, Paolo F. Caimi, Carlos L. Arteaga, A John Iafrate, Jeffrey Sklar, Richard F. Little, Keith T. Flaherty. NCI-MATCH: A new paradigm in the era of genomic oncology [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr PL03-01.

BACKGROUND It is possible that the relative lack of progress in treatment outcomes among adolescent and young adult (AYA) patients with cancer is caused by a difference in disease biology compared with the corresponding diseases in younger and older individuals. There is evidence that colon cancer is more aggressive and has a poorer prognosis in AYA patients than in older adult patients. METHODS To further understand the molecular basis for this difference, whole‐exome sequencing was conducted on a cohort of 30 adult, 30 AYA, and 2 pediatric colon cancers. RESULTS A statistically significant difference in mutational frequency was observed between AYA and adult samples in 43 genes, including ROBO1 , MYC binding protein 2 ( MYCBP2 ), breast cancer 2 (early onset) ( BRCA2 ), MAP3K3, MCPH1, RASGRP3, PTCH1, RAD9B, CTNND1, ATM, NF1 ; KIT, PTEN , and FBXW7 . Many of these mutations were nonsynonymous, missense, stop‐gain, or frameshift mutations that were damaging. Next, RNA sequencing was performed on a subset of the samples to confirm the mutations identified by exome sequencing. This confirmation study verified the presence of a significantly greater frequency of damaging mutations in AYA compared with adult colon cancers for 5 of the 43 genes ( MYCBP2, BRCA2, PHLPP1, TOPORS , and ATR ). CONCLUSIONS The current results provide the rationale for a more comprehensive study with a larger sample set and experimental validation of the functional impact of the identified variants along with their contribution to the biologic and clinical characteristics of AYA colon cancer. Cancer 2018;124:1070‐82. © 2017 American Cancer Society .

Current staging and risk-stratification methods in oncology, while helpful, fail to adequately predict malignancy aggressiveness and/or response to specific treatment. Increased knowledge of cancer biology is generating promising marker candidates for more accurate diagnosis, prognosis assessment, and therapeutic targeting. To apply these exciting results to maximize patient benefit, a disciplined application of well-designed clinical trials for assessing the utility of markers should be used. In this article, we first review the major issues to consider when designing a clinical trial assessing the usefulness of a predictive marker. We then present two classes of clinical trial designs: the Marker by Treatment Interaction Design and the Marker-Based Strategy Design. In the first design, we assume that the marker splits the population into groups in which the efficacy of a particular treatment will differ. This design can be viewed as a classical randomized clinical trial with upfront stratification for the marker. In the second design, after the marker status is known, each patient is randomly assigned either to have therapy determined by their marker status or to receive therapy independent of marker status. The predictive value of the marker is assessed by comparing the outcome of all patients in the marker-based arm to that of all of the patients in the non–marker-based arm. We present detailed sample size calculations for a specific clinical scenario. We discuss the advantages and disadvantages of the two trial designs and their appropriateness to specific clinical situations to assist investigators seeking to design rigorous, marker-based clinical trials.