Genomic Biomarkers Research Articles

A Critical Review of the Prognostic and Predictive Implications of KRAS and STK11 Mutations and Co-Mutations in Metastatic Non-Small Lung Cancer.

The Kirsten rat sarcoma viral oncogene homolog (KRAS) and serine/threonine kinase 11 (STK11) co-mutations are associated with the diverse phenotypic and heterogeneous oncogenic subtypes in non-small cell lung cancer (NSCLC). Due to extensive mixed evidence, there needs to be a review of the recent KRAS and STK11 mutation literature to better understand the potential clinical applications of these genomic biomarkers in the current treatment landscape. This critical review highlights the clinical studies that have elucidated the potential prognostic and predictive implications of KRAS mutations, STK11 mutations, or KRAS/STK11 co-mutations when treating metastatic NSCLC across various types of treatments (e.g., immune checkpoint inhibitors [ICIs]). Overall, KRAS mutations are associated with poor prognoses and have been determined to be a valid but weak prognostic biomarker among patients diagnosed with NSCLC. KRAS mutations in NSCLC have shown mixed results as a predictive clinical biomarker for immune checkpoint inhibitor treatment. Overall, the studies in this review demonstrate that STK11 mutations are prognostic and show mixed results as predictive biomarkers for ICI therapy. However, KRAS/STK11 co-mutations may predict primary resistance to ICI. Prospective KRAS/STK11-biomarker-driven randomized trials are needed to assess the predictive effect of various treatments on the outcomes for patients with metastatic NSCLC, as the majority of the published KRAS analyses are retrospective and hypothesis-generating in nature.

Analytical Validation and Clinical Utilization of the Oncomine Comprehensive Assay Plus Panel for Comprehensive Genomic Profiling in Solid Tumors

The detection of driver oncogenic variants and the recent identification of tumor-agnostic genomic biomarkers has driven the use of comprehensive genomic profiling (CGP) for disease diagnosis, prognosis, and treatment selection. The Oncomine™ Comprehensive Assay Plus (OCA+) panel uses DNA and RNA to detect single nucleotide variants (SNVs), small insertions/deletions (Indels), and structural variants (SVs) across 501 genes. Moreover, microsatellite instability (MSI), tumor mutational burden (TMB), and homologous recombination deficiency (HRD) status are assessed in a single workflow. Herein, we present the analytical validation and clinical utilization of OCA+. By using commercial reference materials, we found good analytical sensitivity, specificity, and precision for all biomarkers analyzed. The limit of detection (LoD) was validated for SNVs and Indels at 4%, except for Indels located in homopolymeric regions, where the LoD was 10%. An additional set of 81 tumor samples, including cytology smears, were sequenced to assess the clinical utility of the OCA+ across different tumor types. Among the clinical cohort, OCA+ demonstrated 100% accuracy, sensitivity, and specificity for all biomarkers analyzed, except for MSI assessment of endometrial cancer cases, where 83% accuracy and 67% sensitivity were achieved, compared to PCR and IHC. The validation of accuracy and robustness of this assay supports the OCA+’s utility for solid tumor CGP.

Identification of genomic biomarkers and their pathway crosstalks for deciphering mechanistic links in glioblastoma.

Glioblastoma is a grade IV pernicious neoplasm occurring in the supratentorial region of brain. As its causes are largely unknown, it is essential to understand its dynamics at the molecular level. This necessitates the identification of better diagnostic and prognostic molecular candidates. Blood-based liquid biopsies are emerging as a novel tool for cancer biomarker discovery, guiding the treatment and improving its early detection based on their tumour origin. There exist previous studies focusing on the identification of tumour-based biomarkers for glioblastoma. However, these biomarkers inadequately represent the underlying pathological state and incompletely illustrate the tumour because of non-recursive nature of this approach to monitor the disease. Also, contrary to the tumour biopsies, liquid biopsies are non-invasive and can be performed at any interval during the disease span to surveil the disease. Therefore, in this study, a unique dataset of blood-based liquid biopsies obtained primarily from tumour-educated blood platelets (TEP) is utilised. This RNA-seq data from ArrayExpress is acquired comprising human cohort with 39 glioblastoma subjects and 43 healthy subjects. Canonical and machine learning approaches are applied for identification of the genomic biomarkers for glioblastoma and their crosstalks. In our study, 97 genes appeared enriched in 7 oncogenic pathways (RAF-MAPK, P53, PRC2-EZH2, YAP conserved, MEK-MAPK, ErbB2 and STK33 signalling pathways) using GSEA, out of which 17 have been identified participating actively in crosstalks. Using PCA, 42 genes are found enriched in 7 pathways (cytoplasmic ribosomal proteins, translation factors, electron transport chain, ribosome, Huntington's disease, primary immunodeficiency pathways, and interferon type I signalling pathway) harbouring tumour when altered, out of which 25 actively participate in crosstalks. All the 14 pathways foster well-known cancer hallmarks and the identified DEGs can serve as genomic biomarkers, not only for the diagnosis and prognosis of Glioblastoma but also in providing a molecular foothold for oncogenic decision making in order to fathom the disease dynamics. Moreover, SNP analysis for the identified DEGs is performed to investigate their roles in disease dynamics in an elaborated manner. These results suggest that TEPs are capable of providing disease insights just like tumour cells with an advantage of being extracted anytime during the course of disease in order to monitor it.

Challenges in diagnosis and biomarker testing for RET-altered lung and thyroid cancer care: an international mixed-method study

BackgroundThe introduction of new targeted therapies for RET-altered lung and thyroid cancers (LC/TC) has impacted pathologists’ practice by making genomic testing more relevant. Variations in health systems and treatment access result in distinct clinical challenges and barriers. This study aimed to assess practice gaps and challenges experienced by pathologists involved in the diagnosis of RET-altered LC/TC, including biomarker testing, to inform educational solutions.MethodsPathologists in Germany, Japan, the UK, and US participated in this ethics-approved mixed-methods study, which included interviews and surveys (data collected January-March 2020). Qualitative data was thematically analysed, quantitative data was analysed with chi-square and Kruskal–Wallis H-tests, and both were triangulated.ResultsA total of 107 pathologists took part in this study. Knowledge gaps were reported regarding genomic testing for LC/TC in Japan (79/60%), the UK (73/66%), and the US (53/30%). Skill gaps were reported when selecting genomic biomarker tests to diagnose TC in Japan (79%), the UK (73%) and US (57%) and when performing specific biomarker tests, especially in Japan (82% for RET) and in the UK (75% for RET). Japanese participants (80%) reported uncertainty about what information to share with the multidisciplinary team to ensure optimal patient-centered care. At the time of data collection, pathologists in Japan faced access barriers to using RET biomarker tests: only 28% agreed that there are relevant RET genomic biomarker tests available in Japan, versus 67% to 90% in other countries.ConclusionsThis study identified areas where pathologists need additional continuing professional development opportunities to enhance their competencies and better support delivery of care to patients with RET-altered lung or thyroid tumours. Addressing identified gaps and improving competencies of pathologists in this field should be emphasised in continuing medical education curricula and through quality improvement initiatives. Strategies deployed on an institutional and health system level should aim to improve interprofessional communication and genetic biomarker testing expertise.

PD-1 Overexpression in Sézary Syndrome Is Epigenetically Regulated

PD-1 Overexpression in Sézary Syndrome Is Epigenetically Regulated

17th International Conference on Malignant Lymphoma, Palazzo dei Congressi, Lugano, Switzerland, 13 - 17 June, 2023.

Introduction: Patient stratification based on genomic biomarkers is critical to optimize treatment of chronic lymphocytic leukemia (CLL). Using digitized, genomically annotated peripheral blood smears (PBS) of patients with CLL, we evaluated whether deep learning can predict presence of TP53 aberrations (del[17p] and/or TP53 mutation) and unmutated IGHV status solely based on cytomorphology. Methods: The workflow consisted of sample collection and digitization, manual annotation, segmentation, morphological feature extraction, and aberration classification. Whole slide images were generated from PBS of 414 patients with previously untreated CLL (CLL14, GIVe, BAAG). Manual annotation was conducted using Qupath software (v0.3.2) with ImageJ. A tailored Stardist model was used for semantic segmentation. Morphological features were collected from each segmented white blood cell (WBC) and fed into the classification model. Two neural network (NN) models were generated for each aberration (TP53 and IGHV) based on a cohort split into 70/30% training and testing datasets. The models were evaluated using AUC (Area Under the Curve of ROC [Receiver Operating Curve]). Results: In preparation of model training, 4,962 manual cells from 18 randomly selected patients were manually annotated. For the TP53 classifier, 141,873 WBC from 52 patients were segmented using the Stardist model. For the IGHV classifier, 131,410 WBC from 57 patients were segmented. The model was trained on 256 × 256 pixels patches obtained from original images with 200 epochs and 100 batch_size whilst making use of data augmentation. An intersection over union (IoU) value of 89.6% confirmed good model performance, i.e. accurate WBC segmentation. Lymphocyte cells were then segmented on each frame image. In total, 28 single-cell morphological features were captured and 8 best representatives fed into the NN model. The collected metadata vector features were randomly assigned to non-overlapping training and testing sets. Separate datasets were used for the TP53 and IGHV classifier. On a single-cell level, the models achieved an AUC of 86% for TP53 aberrations and IGHV status, respectively. For independent validation, the TP53 and IGHV classifiers were tested on a set of unseen images of 33 and 22 patients, respectively. AUC values of 78% and 72%, respectively, were achieved, confirming good model performance. To classify individual patients, a threshold of ≥50% positive cells/image was used to either classify a patient as TP53 aberrated or IGHV unmutated. Using this approach, 70% of patients with TP53 aberration and 68% with IGHV unmutated status were accurately classified. Keywords: Bioinformatics, Chronic Lymphocytic Leukemia (CLL), Computational and Systems Biology, Diagnostic and Prognostic Biomarkers No conflicts of interests pertinent to the abstract.

A pilot phase II trial of neoadjuvant camrelizumab plus nab-paclitaxel and cisplatin (NeoCPC) for locoregionally advanced, resectable squamous cell carcinoma of the head and neck.

6069 Background: For resectable squamous cell carcinoma of the head and neck (HNSCC), novel therapeutic approaches are still needed to improve outcomes. Neoadjuvant immunochemotherapy (NICT) is considered as a potentially effective strategy. We therefore conducted a pilot phase II trial to explore the efficacy and safety of neoadjuvant camrelizumab plus nab-paclitaxel and cisplatin (NeoCPC) in patients with locoregionally advanced, resectable HNSCC. Methods: In this open-label phase II trial, patients with untreated locoregionally advanced, resectable HNSCC (T2‒T4, N0‒N3b, M0; AJCC, 8th Edition) received NICT with camrelizumab (200 mg), nab-paclitaxel (260 mg/m2) and cisplatin (60 mg/m2) on day 1 of each 21-day cycle for three cycles, followed by radiotherapy or surgery. The primary endpoint was objective response rate (ORR) per RECIST version 1.1. Secondary endpoints included pathologic complete response (pCR), major pathologic response (MPR), safety, disease-free survival (DFS), and overall survival (OS). Genomic biomarkers (genetic mutations, tumour mutational burden [TMB] and immune microenvironment) in baseline tumor samples were explored. Results: Between April 2021 and January 2022, 48 patients were enrolled (median age, 59 years [range 27–73]; 42 men [87.5%]). After completion of neoadjuvant therapy, patients underwent surgery (27, 56.3%), chemoradiotherapy (15, 31.2%), radiotherapy (five, 10.4%) or continued immunochemotherapy as maintenance therapy (one, 2.1%). At a median follow-up time of 415 days, the ORR was 89.6% (43/45). Of the 27 patients who had surgery, 17 (63.0%) patients had an MPR, including 15 (55.6%) with a pCR. Patients with ORR were more likely to achieve pCR. One patient died of lung metastasis 6 months after completion of treatment. The 1-year OS and DFS rates were both 97.9%. Only 3 (6.3%) patients had grade 3 treatment-related adverse events (AEs): one with pneumonitis and two with neurotoxicity. No unexpected immune-related AEs were observed. For genetic analysis, the most frequently mutated genes were TP53 (77.1%), CDKN2A, FAT1, CCND1 and NOTCH1. The lower radiographic tumor regression percentage was observed in TP53-altered ( p= 0.01) and TERT-altered ( p= 0.002) patients, whereas higher percentage was observed in HPV-positive patients. The median TMB was 3.15 mutations/MB. No significant difference was observed in TMB between patients with ORR and non-ORR (stable disease). There was a significant correlation between density of M1-like macrophage cells, CD8+ T cells in tumor area and radiographic tumor regression percentage ( p= 0.009, p= 0.0005, respectively). Conclusions: NeoCPC showed promising efficacy with a high ORR and pathologic response rate for locoregionally advanced, resectable HNSCC, with an acceptable safety profile. Clinical trial information: NCT04826679 .

Genomic biomarker testing and treatment in advanced NSCLC: Practice patterns and barriers in a global survey of oncology point-of-care mobile app users.

e21004 Background: Appropriate molecular testing and oncogene-directed treatment planning are essential best practices for managing patients with advanced non-small cell lung cancer (aNSCLC) who are potential candidates for targeted therapy. Understanding real-world practices and challenges among oncology health care professionals (HCPs) is necessary to inform the development of digital tools and other initiatives that support optimal care. Methods: From 12/2022 to 01/2023, 142 HCPs who treat aNSCLC completed an online survey related to NSCLC genomic biomarker testing and treatment planning. Participants were recruited from a global cohort of HCPs who are active users of an oncology point-of-care mobile app following the launch of an NSCLC decision-support tool and educational intervention. Results: Participants included medical oncologists (87%), surgical oncologists (3%), pulmonologists (2%), and nurses (4%) from 62 countries. Most (72%) reported providing care for ≥5 pts/month with aNSCLC; 27.5% provide care for ≥20 pts/month. HCPs reported testing the following genomic biomarkers in 100%, 50-99%, 1-49%, and 0% of patients with aNSCLC, respectively: EGFR (44%, 23%, 27%, 4%), ALK (41%, 20%, 29%, 8%), ROS1 (32%, 19%, 23%, 22%), BRAF (23%, 20%, 23%, 31%), NTRK (12%, 14%, 22%, 47%), HER2 (11%, 17%, 27%, 42%), KRAS (23%, 15%, 25%, 33%), RET (13%, 13%, 25%, 44%), MET exon 14 (15%, 12%, 27%, 42%). Reported barriers varied in frequency (Table 1), with the most common involving biomarker test turnaround time. The majority of HCPs reported often or sometimes feeling that “results take too long,” and they (80%) and/or their patients (81%) are eager to start treatment. HCPs also commonly reported often or sometimes not being sure about which tests to order (45%), when to test (43%), which 1st-line therapy to select (45%), which 2nd- or later-line therapy to select (57%), and how to manage adverse events of oncogene-targeted therapy (50%). Conclusions: In current real-world practice, the majority of HCPs report suboptimal testing for targetable genomic alterations ( EGFR, ALK, ROS1, BRAF, NTRK, HER2, KRAS, RET, and MET exon 14) in patients with aNSCLC. Identified common barriers represent opportunities for future interventions to improve biomarker-directed NSCLC care. [Table: see text]

Perioperative therapy landscape for locally advanced, resectable esophageal cancer: an updated literature review.

The poor oncologic outcomes associated with esophageal cancer (EC) are primarily due to its presentation at an advanced stage and patient comorbidities. While multimodal therapy improves overall outcomes, there is a lack of uniform practice in terms of perioperative management, partly because this is a rapidly evolving field in a heterogeneous patient population. With numerous recent studies incorporating precision medicine with radiographic, pathologic, and genomic biomarkers and with emerging trials using targeted therapies, it is necessary for providers who care for these patients to be familiar with the current and evolving treatment standards to optimize patient outcomes. The objective of this paper is to perform an updated review of the main historical and recently emerging studies that impact the perioperative management of patients with locally advanced, upfront-resectable EC. We mined and reviewed PubMed and American Society of Clinical Oncology databases for pivotal works shaping the current perioperative treatment landscape in locally advanced EC. EC are a vastly heterogeneous disease, and treatment options vary based on tumor anatomic location, histology, and patient comorbidities. Perioperative chemotherapy (CTX), chemoradiation (CRT), and, recently, immunotherapy have improved survival in patients with locally advanced disease. However, optimizing sequencing, de-escalating therapy, and incorporating novel targeted therapies in the perioperative setting are promising strategies that are under ongoing investigation to improve patient outcomes further. There is an ongoing need to identify predictive biomarkers and novel treatment strategies to personalize perioperative approaches and optimize outcomes of patients with EC.

Biomarkers of response to sacituzumab govitecan (SG) and efficacy after treatment with enfortumab vedotin (EV) in advanced urothelial carcinoma (aUC): Analysis of the UNITE study.

4572 Background: SG is an antibody-drug conjugate (ADC) with accelerated FDA approval for aUC refractory to platinum-based chemotherapy and immune checkpoint inhibitor (ICI). SG activity following treatment with EV, the most commonly used ADC in the post-platinum/ICI setting, and biomarkers of response to SG are not well described. We hypothesized that SG would be active after EV in aUC. Methods: Patients (pts) treated with SG monotherapy who had next-generation sequencing (NGS), were identified in the retrospective UNITE study. Observed response rate (ORR) was determined for evaluable pts with scans after ≥1 SG cycle. All pts were assessed for baseline clinical characteristics, as well as molecular biomarkers including tumor mutational burden, somatic gene alterations (alt) in ≥ 10% of pts and presence of ≥1 DNA damage response (DDR) mutations. ORRs were compared with Chi-squared test. Kaplan Meier method and cox proportional hazard (cph) models were used to assess progression-free survival (PFS) and overall survival (OS) from SG start. Pt characteristics and molecular biomarkers were evaluated in univariate analyses (UVA), followed by evaluation of biomarkers in separate multivariate cph analyses (MVA), while accounting for clinical features. Results: Among 90 pts treated with SG at 9 US sites, 78 had NGS data. Median age at SG start was 68, 65 (72%) men, 73 (81%) Caucasian, 56 (62%) with pure urothelial histology, 60 (67%) primary bladder tumor and 67 (74%) ECOG PS 0/1. Most (n=84, 93%) received SG after EV, and 33 (37%) had ≥4 prior therapies for aUC. ORR with SG was 23% (15/66); 24% in pts with prior CR/PR/SD on EV and 14% after primary PD on EV. Median follow-up from SG start was 8.7 mos, PFS and OS were 3.5 mos and 7.1 mos. In pts with NGS, ORRs to SG were higher in MTAP altered pts (50% vs 19%; p = 0.05). In UVA, low neutrophil to lymphocyte ratio (NLR), high Hgb, no prior smoking history, < 3 prior therapies, as well as BRCA2 and DDR alts were associated with longer OS (p<0.05 for all). In MVA, pts with alt in either TP53 or MDM2 had longer OS. Conclusions: SG has notable activity after EV in heavily pretreated pts with aUC, with ORR consistent with SG phase 2 trial data in post-platinum/ICI only pts. We identified several clinical and genomic biomarkers, including TP53/MDM2 alt, that are potentially associated with improved outcomes with SG treatment. [Table: see text]

FUTURE-SUPER: A randomized, subtyping-based umbrella phase II trial for first-line treatment of metastatic triple-negative breast cancer.

3011 Background: Triple-negative breast cancers (TNBCs) are heterogeneous in molecular drivers and immune traits. Our previous studies classified TNBCs into four subtypes (luminal androgen receptor, LAR; immunomodulatory, IM; basal-like immune-suppressed, BLIS; and mesenchymal-like, MES). The subtyping-based treatment strategy was proved clinically feasible, with promising efficacy (Cell Res 2021, NCT03805399) in patients with heavily pretreated metastatic TNBC (mTNBC). Here, we conducted FUTURE-SUPER, a multi-cohort, randomized trial to further evaluate the efficacy of subtyping-based therapy in the first-line treatment of mTNBC. Methods: Patients with untreated locally recurrent inoperable or mTNBC were enrolled. After categorization into 5 cohorts according to TNBC subtypes and genomic biomarkers, patients were randomly assigned (in a 1:1 ratio) to receive nab-paclitaxel (control group) or nab-paclitaxel plus subtyping-based treatment (subtyping-based group): pyrotinib (LAR-HER2 mut), everolimus (LAR- PI3K/AKTmut), camrelizumab and famitinib (IM), bevacizumab (BLIS/MES- PI3K/AKT WT), everolimus (MES- PI3K/AKT mut). The primary endpoint was progression-free survival (PFS). Secondary endpoints included PFS in each subtyping-based cohort, objective response rate (ORR), overall survival (OS) and safety. Results: Between July 29, 2020, and October 17, 2022, 139 patients were enrolled and randomly assigned. With a median follow-up of 18.5 mo (range, 3.5 to 30.3), 101 (72.7%) events of disease progression or death occurred. Median PFS was significantly longer in the subtyping-based group than in the control (11.3 mo vs 5.8 mo; hazard ratio [HR], 0.38; 95% confidence interval [CI], 0.25 to 0.57; P<0.0001). Greater magnitude of PFS benefits were seen for the IM (median, 15.1 mo vs 6.5 mo; HR 0.37; 95% CI, 0.19 to 0.73), BLIS (median, 9.4 mo vs 3.9 mo; HR 0.41; 95% CI, 0.16 to 0.56) and LAR- PI3K/AKT mut (median, 19.1 mo vs 8.4 mo; HR 0.42; 95% CI, 0.12 to 1.53) subtypes. The ORR (measurable-disease population) was higher in the subtyping-based group than in the control group (80.0% [48/60] vs. 44.8% [26/58]; odds ratio, 0.20; 95% CI, 0.09 to 0.46). OS data were not mature. Most adverse events were of grade 1 or 2. Grade 3 and 4 toxicities were as expected, with neutropenia more frequently reported in the subtyping-based group (56.5% vs 26.1%). No treatment-related deaths were recorded. Further high-throughput biomarker analyses are ongoing. Conclusions: Subtyping-based precision treatment significantly prolonged PFS versus nab-paclitaxel in the first-line treatment of advanced TNBC, with manageable toxicities. Our findings highlight the profound clinical benefits with treatment optimization according to molecular/immunological subtypes in TNBC, outlining a direction for further exploration. Clinical trial information: NCT04395989 .

Differential genomic and transcriptomic analysis of invasive lobular and ductal carcinomas.

579 Background: Invasive lobular carcinoma (ILC) is more aggressive than hormone receptor (HR)-positive invasive ductal carcinoma (IDC). However, in practice, ILC and IDC are often treated in a similar fashion with endocrine therapy and chemotherapy. Identifying novel biomarkers, genetic alterations, transcriptomic features, and tumor microenvironment (TME) variations could initiate the development of personalized treatment plans for patients with ILC. Methods: We collected ILC and luminal (non-basal/non-HER2) IDC samples from four datasets (TCGA, METABRIC, RATHER PMC4700448, and UQCCR PMC31263747) and performed differential expression and gene set enrichment analyses, revealing novel genomic, transcriptomic, and TME differences. Using methods from Bagaev et al., we quantified the activity of 29 functional gene expression signatures with single sample gene set enrichment analysis before clustering the samples into five TME subtypes; statistical significance was measured with the Mann-Whitney U test. Differential expression analysis of RNA-Seq data was completed using DESeq2. Further, we analyzed the frequency of specific biomarkers to identify potential therapeutic options. Mutations and biomarker enrichment were assessed using the chi-squared test. Results: We analyzed 1,735 samples (1,442 luminal IDCs and 293 ILCs). CDH1 mutations were more prevalent in ILC samples (56%) compared to IDC samples (6%). Of the 44% of ILC samples with wild-type CDH1, 90% had low CDH1 expression. Inference models showed differences in transcription factors expression between ILC and IDC. ILC had significantly higher expression of TFAP2B, SOCS2, NOSTRIN, THBS4, SCUBE2, and GDF9 and lower expression of CDCA4, PSMG1, LMOD1, and SLC7A5 (adj p < 0.0001 for all genes). Analysis of the TME showed that 44% of ILC samples were immune enriched with high PDL1, CTLA4, and LAG3 expression. In comparison, approximately 30% of ILC samples contained enhanced vascularization and expressed high VEGFA, PDGFRA, and PDGFRB. Finally, compared to luminal IDC, ILC tend to have a statistically significant higher TROP2 expression, similar to that seen in basal subtype. Conclusions: ILC and IDC expressed distinct genomic alterations, gene expression, transcriptomic features, TMEs, and biomarkers. These differences can be used as a blueprint to tailor ILC phenotype-specific interventional clinical trials.

Genomic alterations associated with response to immune checkpoint inhibitors in rare cancers: A biomarker exploration study from the Australian Molecular Screening and Therapeutics (MoST) Program.

2594 Background: Despite immune checkpoint inhibitors (ICI) demonstrating efficacy in over 15 cancer types, evidence in most rare cancers remain scarce, reflecting the challenges of conducting prospective trials. This Australia-wide study reports real-world (RW) objective responses to ICIs targeting the programmed death-(ligand)1 (PD-1/PD-L1) pathway in a large precision oncology program, and associations between response and genomic alterations in rare cancers. Methods: This study was conducted within the framework of the MoST Program (ACTRN12616000908437), where adult patients (pts) with advanced solid tumors were screened using comprehensive genomic profiling (CGP). Only pts who received ICI after CGP were included in this analysis. The best overall response (BOR) to ICI was reported by the treating oncologist during the follow-up period. Best response was categorized as complete (CR), partial (PR), stable (SD), or progressive (PD). Two categories were defined: responders were individuals reported to have experienced CR or PR, while non-progressors were those with CR, PR, or SD. The association between tumor mutational burden (TMB) and response categories was assessed by area under the receiver operator characteristic curve (AUC). Odds ratios (OR) of specific genomic alterations associated with each category were also estimated. Results: Between Dec 2016 and Aug 2022, 4343 pts were screened; 3471 (80%) rare cancer pts, of whom 556 went on to 90 different ICI trials after undergoing CGP. In 273 pts treated with ICI where BOR was reported by the treating oncologist, the median survival was 17.3 months (95% CI 15.0 to 20.4). 13 pts (4.8%) had CR reported, including 8 pts with unapproved indications: 3 sarcomas, and 1 each, small cell carcinoma of unknown primary, adenoid cystic carcinoma, pituitary adenoma, thymoma, and pancreatic adenocarcinoma. 45 (16.5%) and 112 (41.0%) had PR and SD reported, respectively. High TMB, defined as ≥10 non-synonymous tumor mutations/megabase, was identified in 39 (14.3%) pts. TMB was associated with response (AUC 0.715, 0.630 to 0.800) and non-PD (AUC 0.600, 0.528 to 0.671) to ICI. Further exploratory analyses identified that alterations in EP300 (n = 7, OR, 9.8, 1.9 to 52), PTCH1 (n = 6, OR, 15.5, 1.7 to 141) , MSH6 and KMT2D (n = 6 each, OR, 7.7, 1.4 to 43) , and NF1 (n = 10, OR, 3.89, 1.1 to 13.9) were associated with CR/PR. Genomic ARID1A alterations (n = 18) were associated with non-PD (OR 5.16, 1.2 to 22.9), as were alterations in the SWI/SNF complex (n = 20, OR 3.64, 95% CI 1.0 to 12.8) . Conclusions: Notwithstanding their limitations, these real-world data suggest that rare cancer patients may also benefit from ICI. Further prospective investigations into pan-cancer genomic biomarkers of response are warranted. Clinical trial information: ACTRN12616000908437 .

Aggregated analysis of 1,000 patients with cancer to assess the benefits of integrated whole exome and whole transcriptome sequencing.

3076 Background: As the field of precision medicine rapidly expands, clinical oncologists are turning to integrated whole transcriptome (WTS) and whole exome (WES) sequencing to identify the most effective treatment options. We performed a retrospective cohort analysis of WES and WTS data from 1,000 patients with 15 major cancer types to define meaningful relationships between transcriptomic-based tumor microenvironment (TME) subtypes and pan-cancer genomic biomarkers, such as tumor mutational burden (TMB) and microsatellite instability (MSI) status, that are prognostic for outcome and predictive for checkpoint inhibitor response. Methods: We retrospectively analyzed WES/WTS data from cancer patients for biomarkers using our internal bioinformatics workflow. Using transcriptome-based methods described by Bagaev et al., samples were classified into one of four TME subtypes prognostic of patient outcome ( Cancer Cell, 2021). Statistical analysis consisted of Spearman’s rank correlation. Results: Comprehensive WES and WTS analysis provided by the BostonGene Tumor Portrait Test identified biomarkers based on accepted guidelines specific to the patient's cancer type in 22.5% of cases. In addition, we revealed a correlation between WTS and IHC for cancer-relevant genes, including CDX2 (R = 0.68), KRT7 (R = 0.85), KRT20 (R = 0.86), NECTIN4 (R = 0.81), and TACSTD2 (R = 0.81), indicating WTS may also be beneficial for estimating protein expression levels for cancer-specific biomarkers. Analysis of the TME showed that Fibrotic (F) and Immune Desert (D) were the most common subtypes. The F and D subtypes were linked to poor prognosis and were especially prevalent in liver and pancreatic cancers, respectively. TMB-high and MSI status were more prevalent in the immune-enriched subtypes, Immune-Enriched, Fibrotic (IE/F) and Immune-Enriched, Non-fibrotic (IE), over the less favorable F and D subtypes. The frequency of TMB-high and MSI status also differed in both IE subtypes associated with favorable prognosis, suggesting that TME subtyping provides additional prognostic power independent of TMB-high and MSI status. Conclusions: A deep interrogation of our integrated approach to genomic and transcriptomic profiling confirmed the advantages of a unified molecular analysis of tumor traits. We identified clinically significant biomarkers based on molecular features, demonstrated additional capabilities of TME analysis, and illustrated significant correlations between WTS and IHC data. These findings indicate that comprehensive WTS and WES analysis can assist clinicians in optimizing treatment plans as the landscape of personalized therapy continues to grow. [Table: see text]

Genomic landscape of locally advanced rectal adenocarcinoma: Comparison between before and after neoadjuvant chemoradiation and effects of genetic biomarkers on clinical outcomes and tumor response.

To explore genomic biomarkers in rectal cancer by performing whole-exome sequencing. Pre-chemoradiation (CRT) biopsy and post-CRT surgical specimens were obtained from 27 patients undergoing neoadjuvant CRT followed by definitive resection. Exomes were sequenced to a mean coverage of 30×. Somatic single-nucleotide variants (SNVs) and insertions/deletions (indels) were identified. Tumor mutational burden was defined as the number of SNVs or indels. Mutational signatures were extracted and fitted to COSMIC reference signatures. Tumor heterogeneity was quantified with a mutant-allele tumor heterogeneity (MATH) score. Genetic biomarkers and frequently occurred copy number alterations (CNAs) were compared between pre- and post-CRT specimens. Their associations with tumor regression grade (TRG) and clinical outcomes were explored. Top five mutated genes were APC, TP53, NF1, KRAS, and NOTCH1 for pre-CRT samples and APC, TP53, NF1, CREBBP, and ATM for post-CRT samples. Several gene mutations including RUNX1, EGFR, and TP53 in pre-CRT samples showed significant association with clinical outcomes, but not with TRG. However, no such association was found in post-CRT samples. Discordance of driver mutation status was found between pre- and post-CRT samples. In tumor mutational burden analysis, higher number of SNVs or indels was associated with worse treatment outcomes. Six single-base substitution (SBS) signatures identified were SBS1, SBS30, SBS29, SBS49, SBS3, and SBS44. The MATH score decreased after CRT on paired analysis. Less than half of CNAs frequent in post-CRT samples were present in pre-CRT samples. Pre- and post-CRT samples showed different genomic landscape. Potential genetic biomarkers of pre-CRT samples found in the current analysis call for external validation.

Molecular tumor profiling and therapy selection in advanced gynecological cancers: A retrospective cohort analysis from the Australian Molecular Screening and Therapeutics (MoST) Program.

5526 Background: Gynecological (gyne) cancers are highly diverse with distinct sites of origin and histological subtypes that can limit development of evidence-based therapies. Comprehensive genomic profiling (CGP) has an increasing role in characterizing clinically relevant molecular subsets and in identifying actionable biomarkers with potential to guide therapy selection. Methods: MoST (ACTRN12616000908437) is an Australia-wide precision oncology program for adult patients (pts) with advanced cancers and limited treatment options. Tumor specimens are analysed by CGP and genomic results tiered by the level of evidence supporting matched therapies (https://topograph.info). Pts are followed for subsequent treatment and survival. Here, we present data for the MoST gyne cancer cohort. Results: Between Sept 2016 and Oct 2022, 533 gyne tumors were sequenced, with included pts having a minimum 4 months (mo) follow-up. Key histotypes included: ovarian serous (n=162) and non-serous (n=46) epithelial tumors; uterine carcinomas (n=99) and sarcomas (n=108); cervical carcinomas (n=51); germ cell and sex-cord stromal tumors (n=18); carcinosarcomas (n=33); and vulva/vaginal tumors (n=16). The median number of reported variants was 3 (IQR 2-5) and tumor mutational burden 3.1 mut/Mb (IQR 1.3—5.5, Range 0—284); 9 (2%) tumors were microsatellite unstable; and 22 (4%) had high level loss-of-heterozygosity (confirmed on validated genome-wide assays). The most common pathways involved in this pan-gyne cohort were: p53 (n=287, 54%), PI3K/AKT (n=227, 43%), cell cycle (n=182, 34%), and mitogen-activated protein kinase (n=91, 17%). Pathogenic mutations in BRCA1/2 were identified in 29 tumors (5%; 18 in ovarian serous cancers), whereas 81 tumors (15%) had alterations in other homologous recombination genes, most commonly uterine sarcomas (n=32, 30%). Actionable genomic biomarkers matched to a clinically active treatment (TOPOGRAPH tier 1-3) were identified in 207 (39%) tumors. In 19 pts (3.5%) who received Tier 1-3 matched therapy after CGP, a trend towards longer survival was observed (median OS 22.3 mo, 95% CI 17.3 to not reached) compared to those receiving unmatched therapy (n=65, median OS 14.9 mo, 10.2 to 22.1, p=0.052) following CGP. No OS difference was seen in pts who received matched investigational therapy (Tier 3B/4, n=31, median OS 17.0 mo, 8.1 to NR) versus only unmatched therapy (n=118, median OS 14.0 mo, 11.3 to 22.5; HR 0.97, 0.57 to 1.64; p=0.91). Conclusions: CGP identified actionable genomic results in nearly half of advanced gyne cancers, with enrichment in particular histotypes that supports testing above current standard of care. Trends in prolonged OS with subsequent matched therapies may be better realized with earlier testing and improved drug/clinical trial access.

Genomic therapy matching in rare and refractory cancers: Updated results from a retrospective cohort study in the Molecular Screening and Therapeutic (MoST) program.

1540 Background: Biomarker actionability and therapy matching are two central concepts in precision oncology. However, the best strategy to align therapy with genomic alterations remains unclear. Here we report the updated results from a cohort study conducted in an Australian precision oncology program (MoST, ACTRN12616000908437), examining a therapy matching strategy based on comprehensive genomic profiling (CGP) results. Methods: All patients (pts) with rare or advanced solid tumours undergoing CGP from 2016 to 2021 after exhausting standard treatments were included. The primary outcome was overall survival (OS) from the date of CGP result, estimated using the Kaplan-Meier method. Pts were grouped according to tiers of actionability determined by matching against the TOPOGRAPH knowledge base ( https://topograph.info ) and stratified into clinically active (Tier 1-3, therapies with evidence from prospective trials), investigational (Tier 3B and 4, therapies with evidence from another cancer type, preclinical, or retrospective studies), or unmatched tier groups. To assess between-group differences in OS, hazard ratios (HR) were estimated in a time-varying Cox regression model adjusting for time to initiation of subsequent therapy. Results: This updated analysis included 3,383 pts (79% rare and less common). The median follow-up was 22.6 months (mo). For 2,065 pts who did not receive treatment after CGP, the median OS (mOS) was 8.2 mo (95% CI 7.4 to 9.0). For 1,318 pts who received ≥1 line of therapy after CGP, the mOS was 14.1 mo (13.4 to 15.2). 1,270 pts (38%) carried a genomic alteration linked to clinically active therapies (Tier 1-3). Of these, 116 (3.4%) received matched treatment after CGP, experiencing longer survival compared with 410 (32.2%) that received only unmatched therapy (mOS 21.2 v 12.8 mo, HR 0.58, 0.45 to 0.76, P<0.001). Whilst receiving a matched therapy in the investigational tier group (n=133, T3B/4) did not show significant differences in outcomes (mOS 14.5 v unmatched 12.8 mo, n=536, HR 0.88, 0.72 to 1.08, p=0.24), exploratory analyses identified differences in survival for a subset of 41 pts with Switch/Sucrose Non-Fermentable complex mutations receiving matched Tier 4 therapies (mOS 30.1 v 9.6 mo, HR 0.29, 0.17 to 0.51, P<0.0001). Pts receiving repurposed drugs that matched solely on biomarkers in non-cognate cancer types (Tier 3B) showed no survival difference over unmatched therapy (n=35 v 469, mOS 13.6 v 12.5 mo, HR 0.96, 0.65 to 1.41, p=0.83). Conclusions: This study provides insight into how biomarker-linked therapies can be rationally prioritised in rare and advanced cancer populations. Addressing the barriers of access to Tier 1-3 therapies may broaden the utility of genomic biomarker testing. Off-label drug repurposing without direct supporting evidence should only be undertaken in a clinical trial setting.

Genomic biomarker for the top risk factor of gallbladder cancer, cholelithiasis, in a Latinx population.

e16326 Background: Cholelithiasis or Gallstone disease (GSD), is one of the most common and costly digestive disorders in adults worldwide, presenting 10-20% of the general population but in greater than 30% of Latina and Hispanic American women aged 40 years or older. Moreover, GSD individuals contribute significantly to the incidence and mortality of gallbladder and other digestive system cancers; specifically, the excessive risk of gallbladder cancer is 3-10-fold. Parallel to gallbladder cancer, an appalling female preponderance of GSD has been documented for decades; thus, precisely defining high-risk populations and properly managing patients with GSD would lead to reduced disease burden from GSD and multiple cancers. Several genome-wide association studies (GWAS) in the past have identified genes associated with GSD but few were focused on Latinx population. Methods: To identify genetic risk factors for GSD in Latinx population, we used the Sangre Por Salud cohort (SPS) where participants are Latinx adult individuals aged 18-85 years who were current patients in the Mountain Park Health Center in Arizona. This sample represents historically underrepresented population with low socioeconomic status that are primarily Spanish-speaking, majority being born outside of the US, with low rates of health insurance coverage. A total of 172 GSD cases were identified, each matched with 6 controls (n = 1032) who were people from the same community but without history of GSD diagnosis; matching variables are age at enrollment to SPS, sex, height and weight, dyslipidemia, and HbA1C level indicative of type 2 diabetes. We characterized genome-wide interrogation for biomarkers predicting GSD and contributing to the observed gender disparity by performing a GWAS using a matched case-control design. Results: We identified several novel loci associated with GSD and validated few loci that were reported in previous GWAS. The top 3 loci (MATN2, GPRIN3, GPC6) were strongly associated with GSD in our overall analysis; follow-up pathway enrichment analysis suggests enrichment of GO terms that are associated with immunological pathways, enzymatic processes in gallbladder, liver and gastrointestinal tract and GSD pathology. In a sex-specific analysis, CDHR3 and RPL31P35-SEC61G were identified for females, which have been associated respectively with rhinovirus C infection and HbA1c level in previous studies. Conclusions: Our findings suggest directions towards better and deeper understanding of sex differences in GSD pathology, biological mechanisms, and disease progression among Latinx people. Knowing approximately 80% of gallbladder cancer patients harbored gallstones, our optimal goal is to provide evidence for an innovative strategy to early detect and effectively intervene the modifiable risk factors to reduce gallbladder cancer burden in high risk populations.

IDENTIFICATION OF GENOMIC BIOMARKERS OF DISEASE PROGRESSION AND SURVIVAL IN NEWLY‐DIAGNOSED PRIMARY CNS LYMPHOMA

Introduction: There is a significant unmet need for robust genomic biomarkers that identify patients with newly-diagnosed primary CNS lymphoma (PCNSL) at high risk of progression, both during standard methotrexate-based induction as well as after dose-intensive consolidation. Methods: We performed targeted next-generation sequencing of 529 cancer genes of formalin-fixed, paraffin-embedded tumors from 74 patients with newly diagnosed primary CNS diffuse large B-cell lymphoma using the UCSF500 Cancer Panel and the Institute for Human Genetics CLIA Laboratory. The assay detects structural variants including single nucleotide variants, small insertions and deletions, and copy-number alterations (CNAs). Sixty-four EBV-negative PCNSL patients treated with a standard methotrexate, temozolomide, rituximab (MTR) induction were available for complete analysis. Results: We identified frequent mutations involving MYD88 (77%), CD79B (41.9%), ETV6 (27%) and BTG1 (25.7%) as well as frequent CNA involving 6q loss (62.5%), 9p loss (34.4%) and 12 gain (31.3%). Three genomic alterations were most significantly associated with early disease progression in PCNSL: (1) Alterations at 6p21.3, predominantly copy neutral loss of heterozygosity (CN-LOH) at the HLA Class I (HLA-A, B, C) and Class II loci (HLA-DR, DP, DQ, TAP1) as well as homozygous deletion of HLA Class II; (2) Mutations of tumor suppressor genes BTG1 and ETV6. Overall, these genomic alterations were detected in 28 out of 31 progression events in the cohort. The subgroup with either CN-LOH or homozygous deletion at 6p had the earliest progression, followed by the subgroup with mutations at either BTG1/ETV6 and no 6p CN-LOH or homozygous deletion, compared to no alterations at these 3 loci. 10 of 18 tumors with these alterations at 6p also contained BTG1 and/or ETV6 mutations. Survival analysis demonstrates that the subgroup with 6p CN-LOH or homozygous deletion had the earliest progression, followed by the subgroup with BTG1/ETV6 mutations compared to no alterations at these 3 loci (PFS p = 3.7e-5, OS p = 0.0017, logrank test, Figure 1). Multivariate Cox proportional hazard analysis demonstrated a significant 3.24-fold increased risk of progression with 6p CN-LOH/homozygous deletion or BTG1/ETV6 mutations (p = 3.5e-5, adjusted by Age, KPS, IELSG, MSKCC, IOL, Maintenance, and Consolidation). The research was funded by: National Cancer Institute NIH R01CA139-83-01A1 Keywords: aggressive B-cell non-Hodgkin lymphoma, diagnostic and prognostic biomarkers, genomics, epigenomics, and other-omics No conflicts of interests pertinent to the abstract.

Olaparib (O) + ceralasertib (C) in patients (pts) with metastatic triple-negative breast cancer (mTNBC): Translational analysis of the VIOLETTE trial.

1087 Background: O is a PARP inhibitor approved in a number of tumor types and for use in pts with germline (g) mutations in BRCA ( BRCAm) HER2-negative metastatic breast cancer. C is an inhibitor of DDR kinase ATR. Analysis of VIOLETTE (NCT03330847) in pts with mTNBC showed no improvement in PFS with a combination of C and O vs. O, whether in the context of pathogenic BRCAm, non-BRCA HRR pathway mutations (HRRm), or homologous recombination repair (HRR) wildtype (HRRwt) tumors. We report an exploratory translational analysis of predictive genomic biomarkers of response to O ± C beyond g BRCAm. Methods: Pts received O (300 mg twice daily) ± C (160 mg daily; days 1–7; 28-day cycles) as a second- or third-line treatment option. Pts were prospectively stratified into molecular strata based on pathogenic/likely pathogenic alterations in BRCA1/2 ( BRCAm; n=83) or in ≥1 of 13 selected non- BRCA HRR genes (HRRm; n=40) or HRRwt (n=103) using FoundationOneCDx (F1CDx) sequencing assay of archival tumor sample. Advanced genomic analysis included genome-wide loss of heterozygosity (a marker of HRR deficiency [HRD] with a 16% cut-off to define HRD+ [≥16%] vs HRD− [<16%]), zygosity, and predicted g/somatic (s) status of BRCA and HRR alterations based on a validated computational FMI algorithm. Efficacy was evaluated by blinded independent central review of PFS, RECIST response, and best percentage change from baseline in target lesion size. Results: Out of evaluable pts for origin of BRCAm (n=42), 81% (n=34) were of germline, and 19% (n=8) were of somatic origin. Of pts evaluable for zygosity (n=48), most BRCA alterations were biallelic (90%; n=43), and of pts evaluable for HRD status (n=47), most were HRD+ (94%; n=44). Of HRRwt pts evaluable for HRD status (n=79), 57% were HRD+ (n=45). Responses by biomarker are shown. Responses in BRCAm pts were seen in all subgroups (zygosity, HRD, or g/s origin of mutation), including s BRCAm (ORR: n=3/4 on O; n=2/4 on O+C). Responses were also seen in patients with heterozygous BRCA alteration (n=3/5) by genomic result and in BRCAm/HRD− pts (n=3/3) across both arms. Pts with select HRR genes ( BARD1, RAD51C/D, ATM, CDK12) also achieved responses on O or O+C. Conclusions: Responses to O were seen in pts with both g BRCAm and s BRCAm. Beyond BRCAm, the efficacy of O was observed in pts with alterations in select HRR genes, such as BARD1 or RAD51C/D; further clinical investigation is required. Small sample size and HRD analysis performed on archival tumor samples should be considered limitations. Clinical trial information: NCT03330847 . [Table: see text]