Cancer biomarkers: Emerging trends and clinical implications for personalized treatment.

The integration of cancer biomarkers into oncology has revolutionized cancer treatment, yielding remarkable advancements in cancer therapeutics and the prognosis of cancer patients. The development of personalized medicine represents a turning point and a new paradigm in cancer management, as biomarkers enable oncologists to tailor treatments based on the unique molecular profile of each patient's tumor. In this review, we discuss the scientific milestones of cancer biomarkers and explore future possibilities to improve the management of patients with solid tumors. This progress is primarily attributed to the biological characterization of cancers, advancements in testing methodologies, elucidation of the immune microenvironment, and the ability to profile circulating tumor fractions. Integrating these insights promises to continually advance the precision oncology field, fostering better patient outcomes.

Atlas of clinically distinct cell states and ecosystems across human solid tumors.

Determining how cells vary with their local signaling environment and organize into distinct cellular communities is critical for understanding processes as diverse as development, aging, and cancer. Here we introduce EcoTyper, a machine learning framework for large-scale identification and validation of cell states and multicellular communities from bulk, single-cell, and spatially resolved gene expression data. When applied to 12 major cell lineages across 16 types of human carcinoma, EcoTyper identified 69 transcriptionally defined cell states. Most states were specific to neoplastic tissue, ubiquitous across tumor types, and significantly prognostic. By analyzing cell-state co-occurrence patterns, we discovered ten clinically distinct multicellular communities with unexpectedly strong conservation, including three with myeloid and stromal elements linked to adverse survival, one enriched in normal tissue, and two associated with early cancer development. This study elucidates fundamental units of cellular organization in human carcinoma and provides a framework for large-scale profiling of cellular ecosystems in any tissue.

Noninvasive Early Identification of Therapeutic Benefit from Immune Checkpoint Inhibition.

Although treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICIs) can produce remarkably durable responses, most patients develop early disease progression. Furthermore, initial response assessment by conventional imaging is often unable to identify which patients will achieve durable clinical benefit (DCB). Here, we demonstrate that pre-treatment circulating tumor DNA (ctDNA) and peripheral CD8 T cell levels are independently associated with DCB. We further show that ctDNA dynamics after a single infusion can aid in identification of patients who will achieve DCB. Integrating these determinants, we developed and validated an entirely noninvasive multiparameter assay (DIREct-On, Durable Immunotherapy Response Estimation by immune profiling and ctDNA-On-treatment) that robustly predicts which patients will achieve DCB with higher accuracy than any individual feature. Taken together, these results demonstrate that integrated ctDNA and circulating immune cell profiling can provide accurate, noninvasive, and early forecasting of ultimate outcomes for NSCLC patients receiving ICIs.

Dynamic Risk Profiling Using Serial Tumor Biomarkers for Personalized Outcome Prediction.

Accurate prediction of long-term outcomes remains a challenge in the care of cancer patients. Due to the difficulty of serial tumor sampling, previous prediction tools have focused on pretreatment factors. However, emerging non-invasive diagnostics have increased opportunities for serial tumor assessments. We describe the Continuous Individualized Risk Index (CIRI), a method to dynamically determine outcome probabilities for individual patients utilizing risk predictors acquired over time. Similar to "win probability" models in other fields, CIRI provides a real-time probability by integrating risk assessments throughout a patient's course. Applying CIRI to patients with diffuse large B cell lymphoma, we demonstrate improved outcome prediction compared to conventional risk models. We demonstrate CIRI's broader utility in analogous models of chronic lymphocytic leukemia and breast adenocarcinoma and perform a proof-of-concept analysis demonstrating how CIRI could be used to develop predictive biomarkers for therapy selection. We envision that dynamic risk assessment will facilitate personalized medicine and enable innovative therapeutic paradigms.

Global analysis of shared T cell specificities in human non-small cell lung cancer enables HLA inference and antigen discovery.

To identify disease-relevant T cell receptors (TCRs) with shared antigen specificity, we analyzed 778,938 TCRß chain sequences from 178 non-small cell lung cancer patients using the GLIPH2 (grouping of lymphocyte interactions with paratope hotspots 2) algorithm. We identified over 66,000 shared specificity groups, of which 435 were clonally expanded and enriched in tumors compared to adjacent lung. The antigenic epitopes of one such tumor-enriched specificity group were identified using a yeast peptide-HLA A∗02:01 display library. These included a peptide from the epithelial protein TMEM161A, which is overexpressed in tumors and cross-reactive epitopes from Epstein-Barr virus and E. coli. Our findings suggest that this cross-reactivity may underlie the presence of virus-specific T cells in tumor infiltrates and that pathogen cross-reactivity may be a feature of multiple cancers. The approach and analytical pipelines generated in this work, as well as the specificity groups defined here, present a resource for understanding the T cell response in cancer.

Distinct Hodgkin lymphoma subtypes defined by noninvasive genomic profiling.

The scarcity of malignant Hodgkin and Reed-Sternberg cells hampers tissue-based comprehensive genomic profiling of classic Hodgkin lymphoma (cHL). By contrast, liquid biopsies show promise for molecular profiling of cHL due to relatively high circulating tumour DNA (ctDNA) levels1-4. Here we show that the plasma representation of mutations exceeds the bulk tumour representation in most cases, making cHL particularly amenable to noninvasive profiling. Leveraging single-cell transcriptional profiles of cHL tumours, we demonstrate Hodgkin and Reed-Sternberg ctDNA shedding to be shaped by DNASE1L3, whose increased tumour microenvironment-derived expression drives high ctDNA concentrations. Using this insight, we comprehensively profile 366 patients, revealing two distinct cHL genomic subtypes with characteristic clinical and prognostic correlates, as well as distinct transcriptional and immunological profiles. Furthermore, we identify a novel class of truncating IL4R mutations that are dependent on IL-13 signalling and therapeutically targetable with IL-4Rα-blocking antibodies. Finally, using PhasED-seq5, we demonstrate the clinical value of pretreatment and on-treatment ctDNA levels for longitudinally refining cHL risk prediction and for detection of radiographically occult minimal residual disease. Collectively, these results support the utility of noninvasive strategies for genotyping and dynamic monitoring of cHL, as well as capturing molecularly distinct subtypes with diagnostic, prognostic and therapeutic potential.

Risk of Second Tumors and T-Cell Lymphoma after CAR T-Cell Therapy.

BACKGROUND: The risk of second tumors after chimeric antigen receptor (CAR) T-cell therapy, especially the risk of T-cell neoplasms related to viral vector integration, is an emerging concern. METHODS: We reviewed our clinical experience with adoptive cellular CAR T-cell therapy at our institution since 2016 and ascertained the occurrence of second tumors. In one case of secondary T-cell lymphoma, a broad array of molecular, genetic, and cellular techniques were used to interrogate the tumor, the CAR T cells, and the normal hematopoietic cells in the patient. RESULTS: A total of 724 patients who had received T-cell therapies at our center were included in the study. A lethal T-cell lymphoma was identified in a patient who had received axicabtagene ciloleucel therapy for diffuse large B-cell lymphoma, and both lymphomas were deeply profiled. Each lymphoma had molecularly distinct immunophenotypes and genomic profiles, but both were positive for Epstein-Barr virus and were associated with DNMT3A and TET2 mutant clonal hematopoiesis. No evidence of oncogenic retroviral integration was found with the use of multiple techniques. CONCLUSIONS: Our results highlight the rarity of second tumors and provide a framework for defining clonal relationships and viral vector monitoring. (Funded by the National Cancer Institute and others.).

Integrating genomic features for non-invasive early lung cancer detection.

Radiologic screening of high-risk adults reduces lung-cancer-related mortality1,2; however, a small minority of eligible individuals undergo such screening in the United States3,4. The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq)5, a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent. Compared with tumour-derived mutations, clonal haematopoiesis mutations occur on longer cfDNA fragments and lack mutational signatures that are associated with tobacco smoking. Integrating these findings with other molecular features, we develop and prospectively validate a machine-learning method termed 'lung cancer likelihood in plasma' (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls. This approach achieves performance similar to that of tumour-informed ctDNA detection and enables tuning of assay specificity in order to facilitate distinct clinical applications. Our findings establish the potential of cfDNA for lung cancer screening and highlight the importance of risk-matching cases and controls in cfDNA-based screening studies.

The Myc connection: ES cells and cancer.

Gene profiling experiments have revealed similarities between cancer and embryonic stem (ES) cells. Kim et al. (2010) dissect the gene expression signature of ES cells into three functional modules and find that the Myc module, including genes targeted by Myc-interacting proteins, accounts for most of the similarity between ES and cancer cells.

Downregulation of miRNA-200c links breast cancer stem cells with normal stem cells.

Human breast tumors contain a breast cancer stem cell (BCSC) population with properties reminiscent of normal stem cells. We found 37 microRNAs that were differentially expressed between human BCSCs and nontumorigenic cancer cells. Three clusters, miR-200c-141, miR-200b-200a-429, and miR-183-96-182 were downregulated in human BCSCs, normal human and murine mammary stem/progenitor cells, and embryonal carcinoma cells. Expression of BMI1, a known regulator of stem cell self-renewal, was modulated by miR-200c. miR-200c inhibited the clonal expansion of breast cancer cells and suppressed the growth of embryonal carcinoma cells in vitro. Most importantly, miR-200c strongly suppressed the ability of normal mammary stem cells to form mammary ducts and tumor formation driven by human BCSCs in vivo. The coordinated downregulation of three microRNA clusters and the similar functional regulation of clonal expansion by miR-200c provide a molecular link that connects BCSCs with normal stem cells.

A Review of Immunotherapy for Stage III and Metastatic Non-Small Cell Lung Cancer and the Rationale for the ECOG-ACRIN EA5181 Study.

ECOG-ACRIN EA5181 is a phase III prospective, randomized trial that randomizes patients undergoing chemo/radiation for locally advanced non-small cell lung cancer (LA-NSCLC) to concomitant durvalumab or no additional therapy, with both arms receiving 1 year of consolidative durvalumab. Radiation dose escalation failed to improve overall survival in RTOG 0617. However, conventionally fractionated radiation to 60 Gy with concomitant chemotherapy is associated with a high risk of local failure (38%-46%). It is hoped that concomitant immunotherapy during chemo/radiation can help decrease the risk of local failure, thereby improving overall survival and progression-free survival with acceptable toxicity. In this article, we review conventional chemo/radiation therapy for LA-NSCLC, as well as the quickly evolving world of immunotherapy in the treatment of non-small cell lung cancer and discuss the rationale and study design of EA5181. IMPLICATIONS FOR PRACTICE: This article provides an up-to-date assessment of how immunotherapy is reshaping the landscape of metastatic non-small cell lung cancer (NSCLC) and how the impact of this therapy is now rapidly moving into the treatment of patients with locally advanced NSCLC who are presenting for curative treatment. This article reviews the recent publications of chemo/radiation as well as those combining immunotherapy with chemotherapy and chemo/radiation, and provides a strategy for improving overall survival of patients with locally advanced NSCLC by using concomitant immunotherapy with standard concurrent chemo/radiation.

Circulating Tumor DNA Analysis for Detection of Minimal Residual Disease After Chemoradiotherapy for Localized Esophageal Cancer.

BACKGROUND & AIMS: Biomarkers are needed to risk stratify after chemoradiotherapy for localized esophageal cancer. These could improve identification of patients at risk for cancer progression and selection of additional therapy. METHODS: We performed deep sequencing (CAncer Personalized Profiling by deep Sequencing, [CAPP-Seq]) analyses of plasma cell-free DNA collected from 45 patients before and after chemoradiotherapy for esophageal cancer, as well as DNA from leukocytes and fixed esophageal tumor biopsy samples collected during esophagogastroduodenoscopy. Patients were treated from May 2010 through October 2015; 23 patients subsequently underwent esophagectomy, and 22 did not undergo surgery. We also sequenced DNA from blood samples from 40 healthy control individuals. We analyzed 802 regions of 607 genes for single-nucleotide variants previously associated with esophageal adenocarcinoma or squamous cell carcinoma. Patients underwent imaging analyses 6-8 weeks after chemoradiotherapy and were followed for 5 years. Our primary aim was to determine whether detection of circulating tumor DNA (ctDNA) after chemoradiotherapy is associated with risk of tumor progression (growth of local, regional, or distant tumors, detected by imaging or biopsy). RESULTS: The median proportion of tumor-derived DNA in total cell-free DNA before treatment was 0.07%, indicating that ultrasensitive assays are needed for quantification and analysis of ctDNA from localized esophageal tumors. Detection of ctDNA after chemoradiotherapy was associated with tumor progression (hazard ratio, 18.7; P < .0001), formation of distant metastases (hazard ratio, 32.1; P < .0001), and shorter disease-specific survival times (hazard ratio, 23.1; P < .0001). A higher proportion of patients with tumor progression had new mutations detected in plasma samples collected after chemoradiotherapy than patients without progression (P = .03). Detection of ctDNA after chemoradiotherapy preceded radiographic evidence of tumor progression by an average of 2.8 months. Among patients who received chemoradiotherapy without surgery, combined ctDNA and metabolic imaging analysis predicted progression in 100% of patients with tumor progression, compared with 71% for only ctDNA detection and 57% for only metabolic imaging analysis (P < .001 for comparison of either technique to combined analysis). CONCLUSIONS: In an analysis of cell-free DNA in blood samples from patients who underwent chemoradiotherapy for esophageal cancer, detection of ctDNA was associated with tumor progression, metastasis, and disease-specific survival. Analysis of ctDNA might be used to identify patients at highest risk for tumor progression.

High-throughput sequencing for noninvasive disease detection in hematologic malignancies.

Noninvasive monitoring of minimal residual disease (MRD) has led to significant advances in personalized management of patients with hematologic malignancies. Improved therapeutic options and prolonged survival have further increased the need for sensitive tumor assessment that can inform treatment decisions and patient outcomes. At diagnosis or relapse of most hematologic neoplasms, malignant cells are often easily accessible in the blood as circulating tumor cells (CTCs), making them ideal targets to noninvasively profile the molecular features of each patient. In other cancer types, CTCs are generally rare and noninvasive molecular detection relies on circulating tumor DNA (ctDNA) shed from tumor deposits into circulation. The ability to precisely detect and quantify CTCs and ctDNA could minimize invasive procedures and improve prediction of clinical outcomes. Technical advances in MRD detection methods in recent years have led to reduced costs and increased sensitivity, specificity, and applicability. Among currently available tests, high-throughput sequencing (HTS)-based approaches are increasingly attractive for noninvasive molecular testing. HTS-based methods can simultaneously identify multiple genetic markers with high sensitivity and specificity without individual optimization. In this review, we present an overview of techniques used for noninvasive molecular disease detection in selected myeloid and lymphoid neoplasms, with a focus on the current and future role of HTS-based assays.

Case series of MET exon 14 skipping mutation-positive non-small-cell lung cancers with response to crizotinib and cabozantinib.

The mesenchymal-to-epithelial transition (MET) gene is altered and becomes a driver mutation in up to 5% of non-small-cell lung cancer (NSCLC). We report our institutional experience treating patients with MET exon 14 skipping (METex14) mutations, including responses to the MET inhibitors crizotinib and cabozantinib. We identified cases of NSCLC with METex14 mutations using an institutionally developed or commercial next-generation sequencing assay. We assessed patient and disease characteristics by retrospective chart review. Some patients were treated off-label by the physician with crizotinib or cabozantinib, and tumor responses to these agents were assessed. A total of 15 patients with METex14-mutated NSCLC were identified, predominantly male (n=10) with a smoking history (60%) and a median age of 74.0 years. No other actionable somatic mutations were detected. Stage distribution included 26.7% stage I, 6.7% stage II, 6.7% stage III, and 60.0% stage IV. Among patients treated with crizotinib or cabozantinib (n=6), three patients showed partial response and one patient showed stable disease on the basis of RECIST criteria. Four patients experienced side effects requiring drug holiday, reduction, or cessation. Our findings highlight the diversity in presentation and histology of NSCLC with METex14 mutations, which were found in the absence of other actionable driver mutations. We observed evidence of tumor response to crizotinib and cabozantinib, supporting the previous reports that METex14 mutations in NSCLC are actionable driver events.

Control of inflammation by stromal Hedgehog pathway activation restrains colitis.

Inflammation disrupts tissue architecture and function, thereby contributing to the pathogenesis of diverse diseases; the signals that promote or restrict tissue inflammation thus represent potential targets for therapeutic intervention. Here, we report that genetic or pharmacologic Hedgehog pathway inhibition intensifies colon inflammation (colitis) in mice. Conversely, genetic augmentation of Hedgehog response and systemic small-molecule Hedgehog pathway activation potently ameliorate colitis and restrain initiation and progression of colitis-induced adenocarcinoma. Within the colon, the Hedgehog protein signal does not act directly on the epithelium itself, but on underlying stromal cells to induce expression of IL-10, an immune-modulatory cytokine long known to suppress inflammatory intestinal damage. IL-10 function is required for the full protective effect of small-molecule Hedgehog pathway activation in colitis; this pharmacologic augmentation of Hedgehog pathway activity and stromal IL-10 expression are associated with increased presence of CD4+Foxp3+ regulatory T cells. We thus identify stromal cells as cellular coordinators of colon inflammation and suggest their pharmacologic manipulation as a potential means to treat colitis.

Molecular profiling of single circulating tumor cells from lung cancer patients.

Circulating tumor cells (CTCs) are established cancer biomarkers for the "liquid biopsy" of tumors. Molecular analysis of single CTCs, which recapitulate primary and metastatic tumor biology, remains challenging because current platforms have limited throughput, are expensive, and are not easily translatable to the clinic. Here, we report a massively parallel, multigene-profiling nanoplatform to compartmentalize and analyze hundreds of single CTCs. After high-efficiency magnetic collection of CTC from blood, a single-cell nanowell array performs CTC mutation profiling using modular gene panels. Using this approach, we demonstrated multigene expression profiling of individual CTCs from non-small-cell lung cancer (NSCLC) patients with remarkable sensitivity. Thus, we report a high-throughput, multiplexed strategy for single-cell mutation profiling of individual lung cancer CTCs toward minimally invasive cancer therapy prediction and disease monitoring.

Robust enumeration of cell subsets from tissue expression profiles.

We introduce CIBERSORT, a method for characterizing cell composition of complex tissues from their gene expression profiles. When applied to enumeration of hematopoietic subsets in RNA mixtures from fresh, frozen and fixed tissues, including solid tumors, CIBERSORT outperformed other methods with respect to noise, unknown mixture content and closely related cell types. CIBERSORT should enable large-scale analysis of RNA mixtures for cellular biomarkers and therapeutic targets (http://cibersort.stanford.edu/).

Deactivated CRISPR Associated Protein 9 for Minor-Allele Enrichment in Cell-Free DNA.

BACKGROUND: Cell-free DNA (cfDNA) diagnostics are emerging as a new paradigm of disease monitoring and therapy management. The clinical utility of these diagnostics is relatively limited by a low signal-to-noise ratio, such as with low allele frequency (AF) mutations in cancer. While enriching for rare alleles to increase their AF before sample analysis is one strategy that can greatly improve detection capability, current methods are limited in their generalizability, ease of use, and applicability to point mutations. METHODS: Leveraging the robust single-base-pair specificity and generalizability of the CRISPR associated protein 9 (Cas9) system, we developed a deactivated Cas9 (dCas9)-based method of minor-allele enrichment capable of efficient single-target and multiplexed enrichment. The dCas9 protein was complexed with single guide RNAs targeted to mutations of interest and incubated with cfDNA samples containing mutant strands at low abundance. Mutation-bound dCas9 complexes were isolated, dissociated, and the captured DNA purified for downstream use. RESULTS: Targeting the 3 most common epidermal growth factor receptor mutations (exon 19 deletion, T790M, L858R) found in non-small cell lung cancer (NSCLC), we achieved >20-fold increases in AF and detected mutations by use of qPCR at an AF of 0.1%. In a cohort of 18 NSCLC patient-derived cfDNA samples, our method enabled detection of 8 out of 13 mutations that were otherwise undetected by qPCR. CONCLUSIONS: The dCas9 method provides an important application of the CRISPR/Cas9 system outside the realm of genome editing and can provide a step forward for the detection capability of cfDNA diagnostics.

Prognostic value and molecular correlates of a CT image-based quantitative pleural contact index in early stage NSCLC.

PURPOSE: To evaluate the prognostic value and molecular basis of a CT-derived pleural contact index (PCI) in early stage non-small cell lung cancer (NSCLC). EXPERIMENTAL DESIGN: We retrospectively analysed seven NSCLC cohorts. A quantitative PCI was defined on CT as the length of tumour-pleura interface normalised by tumour diameter. We evaluated the prognostic value of PCI in a discovery cohort (n = 117) and tested in an external cohort (n = 88) of stage I NSCLC. Additionally, we identified the molecular correlates and built a gene expression-based surrogate of PCI using another cohort of 89 patients. To further evaluate the prognostic relevance, we used four datasets totalling 775 stage I patients with publically available gene expression data and linked survival information. RESULTS: At a cutoff of 0.8, PCI stratified patients for overall survival in both imaging cohorts (log-rank p = 0.0076, 0.0304). Extracellular matrix (ECM) remodelling was enriched among genes associated with PCI (p = 0.0003). The genomic surrogate of PCI remained an independent predictor of overall survival in the gene expression cohorts (hazard ratio: 1.46, p = 0.0007) adjusting for age, gender, and tumour stage. CONCLUSIONS: CT-derived pleural contact index is associated with ECM remodelling and may serve as a noninvasive prognostic marker in early stage NSCLC. KEY POINTS: • A quantitative pleural contact index (PCI) predicts survival in early stage NSCLC. • PCI is associated with extracellular matrix organisation and collagen catabolic process. • A multi-gene surrogate of PCI is an independent predictor of survival. • PCI can be used to noninvasively identify patients with poor prognosis.

Noninvasive monitoring of diffuse large B-cell lymphoma by immunoglobulin high-throughput sequencing.

Recent studies have shown limited utility of routine surveillance imaging for diffuse large B-cell lymphoma (DLBCL) patients achieving remission. Detection of molecular disease by immunoglobulin high-throughput sequencing (Ig-HTS) from peripheral blood provides an alternate strategy for surveillance. We prospectively evaluated the utility of Ig-HTS within 311 blood and 105 tumor samples from 75 patients with DLBCL, comparing Ig-HTS from the cellular (circulating leukocytes) and acellular (plasma cell-free DNA) compartments of peripheral blood to clinical outcomes and (18)fluoro-deoxyglucose positron emission tomography combined with computed tomography (PET/CT; n = 173). Clonotypic immunoglobulin rearrangements were detected in 83% of patients with adequate tumor samples to enable subsequent monitoring in peripheral blood. Molecular disease measured from plasma, compared with circulating leukocytes, was more abundant and better correlated with radiographic disease burden. Before treatment, molecular disease was detected in the plasma of 82% of patients compared with 71% in circulating cells (P = .68). However, molecular disease was detected significantly more frequently in the plasma at time of relapse (100% vs 30%; P = .001). Detection of molecular disease in the plasma often preceded PET/CT detection of relapse in patients initially achieving remission. During surveillance time points before relapse, plasma Ig-HTS demonstrated improved specificity (100% vs 56%, P < .0001) and similar sensitivity (31% vs 55%, P = .4) compared with PET/CT. Given its high specificity, Ig-HTS from plasma has potential clinical utility for surveillance after complete remission.