High-dimensional mapping of human CEACAM1 expression on immune cells and association with melanoma drug resistance.

BACKGROUND: Human carcinoembryonic antigen cell adhesion molecule 1 (CEACAM1) is an inhibitory cell surface protein that functions through homophilic and heterophilic ligand binding. Its expression on immune cells in human tumors is poorly understood. METHODS: An antibody that distinguishes human CEACAM1 from other highly related CEACAM family members was labeled with 159Tb and inserted into a panel of antibodies that included specificity for programmed cell death protein 1 (PD1) and PD-L1, which are targets of immunotherapy, to gain a data-driven immune cell atlas using cytometry by time-of-flight (CyTOF). A detailed inventory of CEACAM1, PD1, and PD-L1 expression on immune cells in metastatic lesions to lymph node or soft tissues and peripheral blood samples from patients with treatment-naive and -resistant melanoma as well as peripheral blood samples from healthy controls was performed. RESULTS: CEACAM1 is absent or at low levels on healthy circulating immune cells but is increased on immune cells in peripheral blood and tumors of melanoma patients. The majority of circulating PD1-positive NK cells, innate T cells, B cells, monocytic cells, dendritic cells, and CD4+ T cells in the peripheral circulation of treatment-resistant disease co-express CEACAM1 and are demonstrable as discrete populations. CEACAM1 is present on distinct types of cells that are unique to the tumor microenvironment and exhibit expression levels that are highest in treatment resistance; this includes tumor-infiltrating CD8+ T cells. CONCLUSIONS: To the best of our knowledge, this work represents the first comprehensive atlas of CEACAM1 expression on immune cells in a human tumor and reveals an important correlation with treatment-resistant disease. These studies suggest that agents targeting CEACAM1 may represent appropriate partners for PD1-related pathway therapies.

Some proteins, such as programmed cell death protein 1 (PD1), can stop the immune system from attacking cancer cells, allowing cancers to grow. Therapies targeting these proteins can be highly effective, but tumors can become resistant. It is important to identify factors involved in this resistance to develop improved cancer therapies. Human carcinoembryonic antigen cell adhesion molecule 1 (CEACAM1) is a protein that inhibits an immune response and its levels have been associated with poor patient outcomes. We applied a method that allows for the detection of proteins on a single cell to uncover CEACAM1 patterns in melanoma. We found that increased CEACAM1 expression levels on multiple different immune cell types was associated with tumors that were resistant to therapy. These findings may help us to understand the role of CEACAM1 in cancer and to develop better cancer therapies.

Connecting lab, clinic, and community.

Despite great progress in biomedical research, the health of the US population appears to be getting worse. The United States spends substantially more per capita on health care than other wealthy countries, yet US life expectancy ranks low among its peers. Mortality rates have been increasing for segments of the US population, including those in rural areas, certain racial and ethnic groups, and individuals with low socioeconomic status. A whole-of-society approach is required to address such negative trends and disparities, and the biomedical research enterprise must play a key role.

An orientation to the US National Cancer plan for the research community.

The US National Cancer Act of 1971 designated the director of the National Cancer Institute as responsible for coordinating federal agencies and nonfederal organizations to make progress against cancer. As part of her role, the immediate past director of the National Cancer Institute (MMB) led the development of a National Cancer Plan that was formally released on April 3, 2023. The plan includes 8 aspirational goals "to achieve a society where every person with cancer lives a full and active life and to prevent most cancers so that few people need to face this diagnosis." Research findings provide a foundation for each goal, and research gaps are included in the strategies for meeting each goal. The President's Cancer Panel, also created by the National Cancer Act, conducted an initial assessment of progress toward the plan goals by hearing from 12 organizations at a virtual public meeting on September 7, 2023. The purpose of this commentary is to orient the scientific community to the plan and call attention to related knowledge gaps that could benefit from research.

CALGB 80802 (Alliance): Impact of Sorafenib with and without Doxorubicin on Hepatitis C Infection in Patients with Advanced Hepatocellular Carcinoma.

Sorafenib blocks nonstructural protein 5A (NS5A)-recruited c-Raf-mediated hepatitis C virus (HCV) replication and gene expression. Release of Raf-1-Ask-1 dimer and inhibition of Raf-1 via sorafenib putatively differ in the presence or absence of doxorubicin. Cancer and Leukemia Group B (CALGB) 80802 (Alliance) randomized phase III trial of doxorubicin plus sorafenib versus sorafenib in patients with advanced hepatocellular carcinoma (HCC), showed no improvement in median overall survival (OS). Whether HCV viral load impacts therapy and whether any correlation between HCV titers and outcome based on HCV was studied. In patients with HCV, HCV titer levels were evaluated at baseline and at multiple postbaseline timepoints until disease progression or treatment discontinuation. HCV titer levels were evaluated in relation to OS and progression-free survival (PFS). Among 53 patients with baseline HCV data, 12 patients had undetectable HCV (HCV-UN). Postbaseline HCV titer levels did not significantly differ between treatment arms. One patient in each arm went from detectable to HCV-UN with greater than 2 log-fold titer levels reduction. Aside from these 2 HCV-UN patients, HCV titers remained stable on treatment. Patients who had HCV-UN at baseline were 3.5 times more likely to progress and/or die from HCC compared with HCV detectable (HR = 3.51; 95% confidence interval: 1.58-7.78; P = 0.002). HCV titer levels remained unchanged, negating any sorafenib impact onto HCV titer levels. Although an overall negative phase III study, patients treated with doxorubicin plus sorafenib and sorafenib only, on CALGB 80802 had worse PFS if HCV-UN. Higher levels of HCV titers at baseline were associated with significantly improved PFS. SIGNIFICANCE: Sorafenib therapy for HCC may impact HCV replication and viral gene expression. In HCV-positive patients accrued to CLAGB 80802 phase III study evaluating the addition of doxorubicin to sorafenib, HCV titer levels were evaluated at baseline and different timepoints. Sorafenib did not impact HCV titer levels. Despite an improved PFS in patients with detectable higher level HCV titers at baseline, no difference in OS was noted.

Achieving the Goals of the Cancer Moonshot Requires Progress against All Cancers.

SUMMARY: In February 2022, President Joseph R. Biden made reducing age-adjusted cancer mortality by at least 50% over the next 25 years a key goal of the Cancer Moonshot. Although recent progress puts this goal within reach, succeeding will require major commitments to progress on all fronts: basic research, clinical and translational research, health care delivery, and public health. See related article by Shiels et al., p. 1084 (2).

Gene signatures derived from transcriptomic-causal networks stratified colorectal cancer patients for effective targeted therapy.

Predictive and prognostic gene signatures derived from interconnectivity among genes can tailor clinical care to patients in cancer treatment. We identified gene interconnectivity as the transcriptomic-causal network by integrating germline genotyping and tumor RNA-seq data from 1,165 patients with metastatic colorectal cancer (CRC). The patients were enrolled in a clinical trial with randomized treatment, either cetuximab or bevacizumab in combination with chemotherapy. We linked the network to overall survival (OS) and detected novel biomarkers by controlling for confounding genes. Our data-driven approach discerned sets of genes, each set collectively stratify patients based on OS. Two signatures under the cetuximab treatment were related to wound healing and macrophages. The signature under the bevacizumab treatment was related to cytotoxicity and we replicated its effect on OS using an external cohort. We also showed that the genes influencing OS within the signatures are downregulated in CRC tumor vs. normal tissue using another external cohort. Furthermore, the corresponding proteins encoded by the genes within the signatures interact each other and are functionally related. In conclusion, this study identified a group of genes that collectively stratified patients based on OS and uncovered promising novel prognostic biomarkers for personalized treatment of CRC using transcriptomic causal networks.

Concurrent inhibition of CDK2 adds to the anti-tumour activity of CDK4/6 inhibition in GIST.

BACKGROUND: Advanced gastrointestinal stromal tumour (GIST) is characterised by genomic perturbations of key cell cycle regulators. Oncogenic activation of CDK4/6 results in RB1 inactivation and cell cycle progression. Given that single-agent CDK4/6 inhibitor therapy failed to show clinical activity in advanced GIST, we evaluated strategies for maximising response to therapeutic CDK4/6 inhibition. METHODS: Targeted next-generation sequencing and multiplexed protein imaging were used to detect cell cycle regulator aberrations in GIST clinical samples. The impact of inhibitors of CDK2, CDK4 and CDK2/4/6 was determined through cell proliferation and protein detection assays. CDK-inhibitor resistance mechanisms were characterised in GIST cell lines after long-term exposure. RESULTS: We identify recurrent genomic aberrations in cell cycle regulators causing co-activation of the CDK2 and CDK4/6 pathways in clinical GIST samples. Therapeutic co-targeting of CDK2 and CDK4/6 is synergistic in GIST cell lines with intact RB1, through inhibition of RB1 hyperphosphorylation and cell proliferation. Moreover, RB1 inactivation and a novel oncogenic cyclin D1 resulting from an intragenic rearrangement (CCND1::chr11.g:70025223) are mechanisms of acquired CDK-inhibitor resistance in GIST. CONCLUSIONS: These studies establish the biological rationale for CDK2 and CDK4/6 co-inhibition as a therapeutic strategy in patients with advanced GIST, including metastatic GIST progressing on tyrosine kinase inhibitors.

Linking Genotype to Phenotype: Bench to Bedside.

Over the past three decades, researchers in the NCI-funded cancer cooperative groups have routinely incorporated a collection of biospecimens, quality-of-life assessments, diet and physical activity data, and other health outcome variables from clinical trial participants to provide an expanding resource for correlative science in cancer clinical research. See related articles by Nixon et al., p. 2771 and 2779.

Tumor Immunogenomic Features Determine Outcomes in Patients with Metastatic Colorectal Cancer Treated with Standard-of-Care Combinations of Bevacizumab and Cetuximab.

PURPOSE: CALGB/SWOG 80405 was a randomized phase III trial in first-line patients with metastatic colorectal cancer treated with bevacizumab, cetuximab, or both, plus chemotherapy. We tested the effect of tumor immune features on overall survival (OS). EXPERIMENTAL DESIGN: Primary tumors (N = 554) were profiled by RNA sequencing. Immune signatures of macrophages, lymphocytes, TGFß, IFNγ, wound healing, and cytotoxicity were measured. CIBERSORTx scores of naive and memory B cells, plasma cells, CD8+ T cells, resting and activated memory CD4+ T cells, M0 and M2 macrophages, and activated mast cells were measured. RESULTS: Increased M2 macrophage score [HR, 6.30; 95% confidence interval (CI), 3.0-12.15] and TGFß signature expression (HR, 1.35; 95% CI, 1.05-1.77) were associated with shorter OS. Increased scores of plasma cells (HR, 0.55; 95% CI, 0.38-0.87) and activated memory CD4+ T cells (HR, 0.34; 95% CI, 0.16-0.65) were associated with longer OS. Using optimal cutoffs from these four features, patients were categorized as having either 4, 3, 2, or 0-1 beneficial features associated with longer OS, and the median (95% CI) OS decreased from 42.5 (35.8-47.8) to 31.0 (28.8-34.4), 25.2 (20.6-27.9), and 17.7 (13.5-20.4) months respectively (P = 3.48e-11). CONCLUSIONS: New immune features can be further evaluated to improve patient response. They provide the rationale for more effective immunotherapy strategies.

Genomic Analysis of Germline Variation Associated with Survival of Patients with Colorectal Cancer Treated with Chemotherapy Plus Biologics in CALGB/SWOG 80405 (Alliance).

PURPOSE: Irinotecan/5-fluorouracil (5-FU; FOLFIRI) or oxaliplatin/5-FU (FOLFOX), combined with bevacizumab or cetuximab, are approved, first-line treatments for metastatic colorectal cancer (mCRC). We aimed at identifying germline variants associated with survival in patients with mCRC treated with these regimens in Cancer and Leukemia Group B/SWOG 80405. EXPERIMENTAL DESIGN: Patients with mCRC receiving either FOLFOX or FOLFIRI were randomized to either cetuximab or bevacizumab. DNA from peripheral blood was genotyped for approximately 700,000 SNPs. The association between SNPs and overall survival (OS) was tested in 613 patients of genetically estimated European ancestry using Cox proportional hazards models. RESULTS: The four most significant SNPs associated with OS were three haplotypic SNPs between microsomal glutathione S-transferase 1 (MGST1) and LIM domain only 3 (LMO3, representative HR, 1.56; P = 1.30 × 10-6), and rs11644916 in AXIN1 (HR, 1.39, P = 4.26 × 10-6). AXIN1 is a well-established tumor suppressor gene in colorectal cancer, and rs11644916 (G>A) conferred shorter OS. Median OS for patients with the AA, AG, or GG genotypes was 18.4, 25.6, or 36.4 months, respectively. In 90 patients with stage IV colorectal cancer from The Cancer Genome Atlas (TCGA), rs11649255 in AXIN1 [in almost complete linkage disequilibrium (LD) with rs11644916], was associated with shorter OS (HR, 2.24, P = 0.0096). Using rs11648673 in AXIN1 (in very high LD with rs11644916 and with functional evidence), luciferase activity in three colorectal cancer cell lines was reduced. CONCLUSIONS: This is the first large genome-wide association study ever conducted in patients with mCRC treated with first-line standard treatment in a randomized phase III trial. A common SNP in AXIN1 conferred worse OS and the effect was replicated in TCGA. Further studies in colorectal cancer experimental models are required.

Composite grading algorithm for the National Cancer Institute's Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE).

BACKGROUND: The Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events is an item library designed for eliciting patient-reported adverse events in oncology. For each adverse event, up to three individual items are scored for frequency, severity, and interference with daily activities. To align the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events with other standardized tools for adverse event assessment including the Common Terminology Criteria for Adverse Events, an algorithm for mapping individual items for any given adverse event to a single composite numerical grade was developed and tested. METHODS: A five-step process was used: (1) All 179 possible Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events score combinations were presented to 20 clinical investigators to subjectively map combinations to single numerical grades ranging from 0 to 3. (2) Combinations with <75% agreement were presented to investigator committees at a National Clinical Trials Network cooperative group meeting to gain majority consensus via anonymous voting. (3) The resulting algorithm was refined via graphical and tabular approaches to assure directional consistency. (4) Validity, reliability, and sensitivity were assessed in a national study dataset. (5) Accuracy for delineating adverse events between study arms was measured in two Phase III clinical trials (NCT02066181 and NCT01522443). RESULTS: In Step 1, 12/179 score combinations had <75% initial agreement. In Step 2, majority consensus was reached for all combinations. In Step 3, five grades were adjusted to assure directional consistency. In Steps 4 and 5, composite grades performed well and comparably to individual item scores on validity, reliability, sensitivity, and between-arm delineation. CONCLUSION: A composite grading algorithm has been developed and yields single numerical grades for adverse events assessed via the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events, and can be useful in analyses and reporting.

What happened to the US cancer cooperative groups? A status update ten years after the Institute of Medicine report.

The US cancer cooperative groups (cooperative groups) were founded in the 1950s to establish a standing infrastructure to conduct multi-institutional cancer clinical trials. Initially funded almost entirely by the US National Cancer Institute (NCI), over the years, the research conducted by the Cooperative Groups has evolved to meet the demands of cancer clinical research, with a scope now encompassing trials to advance cancer treatment, cancer control, biomarker development and validation, and health services research, with a corresponding broadening of their funding sources. The cooperative groups are also a critical mechanism for educating the next generation of cancer clinical trialists from many different disciplines. This review outlines the overall mission, structure, and funding of the cooperative groups, beginning in 1955 when they were first established by the NCI, and describes the considerable progress against cancer achieved over the past decade.

The electronic health record as a clinical trials tool: Opportunities and challenges.

Clinical trials provide evidence essential for progress in health care, and as the complexity of medical care has increased, the demand for such data has dramatically expanded. Conducting clinical trials has also become more complicated, evolving to meet increasing challenges in delivering clinical care and meeting regulatory requirements. Despite this, the general approach to data collection remains the same, requiring that researchers submit clinical data in response to study treatment protocols, using precisely defined data structures made available in study-specific case report forms. Currently, research data management is not integrated within the patient's clinical care record, creating added burden for clinical staff and opportunities for error. During the past decade, the electronic health record has become standard across the US healthcare system and is increasingly used to collect and analyze data reporting quality metrics for clinical care delivery. Recently, electronic health record data have also been used to address clinical research questions; however, this approach has significant drawbacks due to the unstructured and incomplete nature of current electronic health record data. This report describes steps necessary to use the electronic health record as a tool for conducting high-quality clinical research.

Status Update on Data Required to Build a Learning Health System.

Wide adoption of electronic health records (EHRs) has raised the expectation that data obtained during routine clinical care, termed "real-world" data, will be accumulated across health care systems and analyzed on a large scale to produce improvements in patient outcomes and the use of health care resources. To facilitate a learning health system, EHRs must contain clinically meaningful structured data elements that can be readily exchanged, and the data must be of adequate quality to draw valid inferences. At the present time, the majority of EHR content is unstructured and locked into proprietary systems that pose significant challenges to conducting accurate analyses of many clinical outcomes. This article details the current state of data obtained at the point of care and describes the changes necessary to use the EHR to build a learning health system.