Strength in numbers: predicting response to checkpoint inhibitors from large clinical datasets.

The advent of immune checkpoint blockers for cancer therapy has spawned great interest in identifying molecular features reflecting the complexity of tumor immunity, which can subsequently be leveraged as predictive biomarkers. In a thorough big-data approach analyzing the largest series of homogenized molecular and clinical datasets, Litchfield et al. identified a set of genomic biomarkers that identifies immunotherapy responders across cancer types.

FGFR2 Inhibition in Cholangiocarcinoma.

Biliary tract cancer (BTC) is the second most common primary liver cancer after hepatocellular carcinoma and accounts for 2% of cancer-related deaths. BTCs are classified according to their anatomical origin into intrahepatic (iCCA), perihilar, or distal cholangiocarcinoma, as well as gall bladder carcinoma. While the mutational profiles in these anatomical BTC subtypes overlap to a large extent, iCCA is notable for the high frequency of IDH1/2 mutations (10-22%) and the nearly exclusive occurrence of FGFR2 fusions in 10-15% of patients. In recent years, FGFR2 fusions have become one of the most promising targets for precision oncology targeting BTC, with FGFR inhibitors already approved in Europe and the United States for patients with advanced, pretreated iCCA. While the therapeutic potential of nonfusion alterations is still under debate, it is expected that the field of FGFR2-directed therapies will be subject to rapid further evolution and optimization. The scope of this review is to provide an overview of oncogenic FGFR signaling in iCCA cells and highlight the pathophysiology, diagnostic testing strategies, and therapeutic promises and challenges associated with FGFR2-altered iCCA.

A phase 2 clinical trial of combined BRAF/MEK inhibition for BRAFV600E-mutated multiple myeloma.

Activating BRAF mutations are found in a small subset of patients with newly diagnosed multiple myeloma, but prevalence increases in late-stage, refractory disease, and the mutations are associated with adverse outcome. This prospective single-arm, open-label, multicenter phase 2 trial assessed the efficacy and safety of combined BRAF/MEK inhibition, using encorafenib and binimetinib, in patients with relapsed/refractory multiple myeloma (RRMM) carrying a BRAFV600E mutation. Patients received 450 mg encorafenib once daily and binimetinib 45 mg twice daily. The primary end point was the overall response rate achieved within the first year after start of treatment according to International Myeloma Working Group criteria. Twelve RRMM patients with a median of 5 prior lines of therapy were enrolled. The overall response rate was 83.3%, with 10 patients achieving at least a partial response. The median progression-free survival was 5.6 months, and overall survival was 55% at 24 months. Emerging resistance to therapy was driven by RAS mutations and structural variants involving the BRAF locus. This is the first prospective clinical trial to demonstrate that combined BRAF/MEK inhibition is highly effective in patients with BRAFV600E-mutated RRMM, and it represents a successful targeted precision medicine approach in this disease. This trial was registered at www.clinicaltrials.gov as #NCT02834364.

Stratifying esophago-gastric cancer treatment using a patient-derived organoid-based threshold.

BACKGROUND AND AIMS: This study sought to determine the value of patient-derived organoids (PDOs) from esophago-gastric adenocarcinoma (EGC) for response prediction to neoadjuvant chemotherapy (neoCTx). METHODS: Endoscopic biopsies of patients with locally advanced EGC (n = 120) were taken into culture and PDOs expanded. PDOs' response towards the single substances of the FLOT regimen and the combination treatment were correlated to patients' pathological response using tumor regression grading. A classifier based on FLOT response of PDOs was established in an exploratory cohort (n = 13) and subsequently confirmed in an independent validation cohort (n = 13). RESULTS: EGC PDOs reflected patients' diverse responses to single chemotherapeutics and the combination regimen FLOT. In the exploratory cohort, PDOs response to single 5-FU and FLOT combination treatment correlated with the patients' pathological response (5-FU: Kendall's τ = 0.411, P = 0.001; FLOT: Kendall's τ = 0.694, P = 2.541e-08). For FLOT testing, a high diagnostic precision in receiver operating characteristic (ROC) analysis was reached with an AUCROC of 0.994 (CI 0.980 to 1.000). The discriminative ability of PDO-based FLOT testing allowed the definition of a threshold, which classified in an independent validation cohort FLOT responders from non-responders with high sensitivity (90%), specificity (100%) and accuracy (92%). CONCLUSION: In vitro drug testing of EGC PDOs has a high predictive accuracy in classifying patients' histological response to neoadjuvant FLOT treatment. Taking into account the high rate of successful PDO expansion from biopsies, the definition of a threshold that allows treatment stratification paves the way for an interventional trial exploring PDO-guided treatment of EGC patients.

KRAS and TP53 co-mutation predicts benefit of immune checkpoint blockade in lung adenocarcinoma.

BACKGROUND: Predictive biomarkers in use for immunotherapy in advanced non-small cell lung cancer are of limited sensitivity and specificity. We analysed the potential of activating KRAS and pathogenic TP53 mutations to provide additional predictive information. METHODS: The study cohort included 713 consecutive immunotherapy patients with advanced lung adenocarcinomas, negative for actionable genetic alterations. Additionally, two previously published immunotherapy and two surgical patient cohorts were analyzed. Therapy benefit was stratified by KRAS and TP53 mutations. Molecular characteristics underlying KRASmut/TP53mut tumours were revealed by the analysis of TCGA data. RESULTS: An interaction between KRAS and TP53 mutations was observed in univariate and multivariate analyses of overall survival (Hazard ratio [HR] = 0.56, p = 0.0044 and HR = 0.53, p = 0.0021) resulting in a stronger benefit for KRASmut/TP53mut tumours (HR = 0.71, CI 0.55-0.92). This observation was confirmed in immunotherapy cohorts but not observed in surgical cohorts. Tumour mutational burden, proliferation, and PD-L1 mRNA were significantly higher in TP53-mutated tumours, regardless of KRAS status. Genome-wide expression analysis revealed 64 genes, including CX3CL1 (fractalkine), as specific transcriptomic characteristic of KRASmut/TP53mut tumours. CONCLUSIONS: KRAS/TP53 co-mutation predicts ICI benefit in univariate and multivariate survival analyses and is associated with unique molecular tumour features. Mutation testing of the two genes can be easily implemented using small NGS panels.

Deep Learning-Enabled Diagnosis of Liver Adenocarcinoma.

BACKGROUND & AIMS: Diagnosis of adenocarcinoma in the liver is a frequent scenario in routine pathology and has a critical impact on clinical decision making. However, rendering a correct diagnosis can be challenging, and often requires the integration of clinical, radiologic, and immunohistochemical information. We present a deep learning model (HEPNET) to distinguish intrahepatic cholangiocarcinoma from colorectal liver metastasis, as the most frequent primary and secondary forms of liver adenocarcinoma, with clinical grade accuracy using H&E-stained whole-slide images. METHODS: HEPNET was trained on 714,589 image tiles from 456 patients who were randomly selected in a stratified manner from a pool of 571 patients who underwent surgical resection or biopsy at Heidelberg University Hospital. Model performance was evaluated on a hold-out internal test set comprising 115 patients and externally validated on 159 patients recruited at Mainz University Hospital. RESULTS: On the hold-out internal test set, HEPNET achieved an area under the receiver operating characteristic curve of 0.994 (95% CI, 0.989-1.000) and an accuracy of 96.522% (95% CI, 94.521%-98.694%) at the patient level. Validation on the external test set yielded an area under the receiver operating characteristic curve of 0.997 (95% CI, 0.995-1.000), corresponding to an accuracy of 98.113% (95% CI, 96.907%-100.000%). HEPNET surpassed the performance of 6 pathology experts with different levels of experience in a reader study of 50 patients (P = .0005), boosted the performance of resident pathologists to the level of senior pathologists, and reduced potential downstream analyses. CONCLUSIONS: We provided a ready-to-use tool with clinical grade performance that may facilitate routine pathology by rendering a definitive diagnosis and guiding ancillary testing. The incorporation of HEPNET into pathology laboratories may optimize the diagnostic workflow, complemented by test-related labor and cost savings.

Accurate and efficient detection of gene fusions from RNA sequencing data.

The identification of gene fusions from RNA sequencing data is a routine task in cancer research and precision oncology. However, despite the availability of many computational tools, fusion detection remains challenging. Existing methods suffer from poor prediction accuracy and are computationally demanding. We developed Arriba, a novel fusion detection algorithm with high sensitivity and short runtime. When applied to a large collection of published pancreatic cancer samples (n = 803), Arriba identified a variety of driver fusions, many of which affected druggable proteins, including ALK, BRAF, FGFR2, NRG1, NTRK1, NTRK3, RET, and ROS1. The fusions were significantly associated with KRAS wild-type tumors and involved proteins stimulating the MAPK signaling pathway, suggesting that they substitute for activating mutations in KRAS In addition, we confirmed the transforming potential of two novel fusions, RRBP1-RAF1 and RASGRP1-ATP1A1, in cellular assays. These results show Arriba's utility in both basic cancer research and clinical translation.

High-throughput molecular assays for inclusion in personalised oncology trials - State-of-the-art and beyond.

In the last decades, the development of high-throughput molecular assays has revolutionised cancer diagnostics, paving the way for the concept of personalised cancer medicine. This progress has been driven by the introduction of such technologies through biomarker-driven oncology trials. In this review, strengths and limitations of various state-of-the-art sequencing technologies, including gene panel sequencing (DNA and RNA), whole-exome/whole-genome sequencing and whole-transcriptome sequencing, are explored, focusing on their ability to identify clinically relevant biomarkers with diagnostic, prognostic and/or predictive impact. This includes the need to assess complex biomarkers, for example microsatellite instability, tumour mutation burden and homologous recombination deficiency, to identify patients suitable for specific therapies, including immunotherapy. Furthermore, the crucial role of biomarker analysis and multidisciplinary molecular tumour boards in selecting patients for trial inclusion is discussed in relation to various trial concepts, including drug repurposing. Recognising that today's exploratory techniques will evolve into tomorrow's routine diagnostics and clinical study inclusion assays, the importance of emerging technologies for multimodal diagnostics, such as proteomics and in vivo drug sensitivity testing, is also discussed. In addition, key regulatory aspects and the importance of patient engagement in all phases of a clinical trial are described. Finally, we propose a set of recommendations for consideration when planning a new precision cancer medicine trial.

Sarcomas With RAD51B Fusions Are Associated With a Heterogeneous Phenotype.

RAD51B-rearranged sarcomas are rare neoplasms that exhibit a heterogeneous morphology. To date, 6 cases have been reported, all involving the uterus, including 4 perivascular epithelioid cell tumors (PEComas) and 2 leiomyosarcomas (LMS). In this study, we describe the morphologic, immunohistochemical, and molecular features of 8 additional sarcomas with RAD51B rearrangement, including the first extrauterine example. All patients were women with a median age of 57 years at presentation. Seven tumors originated in the uterus, and one in the lower extremity soft tissue, with a median tumor size of 12 cm. Histologically, 4 tumors showed predominantly spindle cell morphology with eosinophilic fibrillary cytoplasm, with or without nuclear pleomorphism, whereas 2 tumors exhibited pleomorphic epithelioid cells, featuring clear to eosinophilic, granular cytoplasm. Two neoplasms exhibited undifferentiated cytomorphology, including one with uniform small blue round cells. All tumors showed high-grade cytologic atypia and high mitotic activity (median: 30/10 high-power fields), whereas coagulative necrosis was noted in 6 cases and lymphovascular invasion in 2. By immunohistochemistry, 2 showed myoid and melanocytic markers in keeping with PEComa, whereas 4 cases were only positive for smooth muscle markers consistent with LMS (including 3 myxoid). The remaining 2 cases had a nonspecific immunoprofile. Five cases tested by targeted RNA sequencing (Archer FusionPlex, Illumina TruSight) showed different fusion partners (HMGA2, PDDC1, and CEP170). RAD51B rearrangements were identified by FISH in the remaining 3 cases. Targeted DNA sequencing in 2 cases was negative for TSC gene alterations. Clinical outcome, available in 5 patients (median follow-up, 19 months), revealed 3 local recurrences, 2 lung metastases, and 4 deaths due to disease. Our results expand the spectrum of sarcomas with RAD51B fusions, demonstrating variable clinical presentations, morphologic spectrum, and fusion partners. These tumors have a predilection for a uterine location, with either LMS, PEComa, or undifferentiated phenotypes, and are associated with an aggressive clinical course.

Frequency and Prognostic Value of Circulating Tumor Cells in Cancer of Unknown Primary.

BACKGROUND: Cancer of unknown primary (CUP) is defined as a primary metastatic malignancy, in which the primary tumor remains elusive in spite of a comprehensive diagnostic workup. The frequency and prognostic value of circulating tumor cells (CTCs), which are considered to be the source of metastasis, has not yet been systematically evaluated in CUP. METHODS: A total of 110 patients with a confirmed diagnosis of CUP according to the European Society for Medical Oncology (ESMO) guidelines, who presented to our clinic between July 2021 and May 2023, provided blood samples for CTC quantification using CellSearch methodology. CTC counts were correlated with demographic, clinical, and molecular data generated by comprehensive genomic profiling of tumor tissue. RESULTS: CTCs were detected in 26% of all patients at initial presentation to our department. The highest CTC frequency was observed among patients with unfavorable CUP (35.5%), while patients with single-site/oligometastatic CUP harbored the lowest CTC frequency (11.4%). No statistically significant association between CTC positivity and the number of affected organs (P = 0.478) or disease burden (P = 0.120) was found. High CTC levels (≥5 CTCs/7.5 mL; 12/95 analyzed patients) predicted for adverse overall survival compared to negative or low CTC counts (6-months overall survival rate 90% vs 32%, log-rank P < 0.001; HR 5.43; 95% CI 2.23-13.2). CTC dynamics were also prognostic for overall survival by landmark analysis (log-rank P < 0.001, HR 10.2, 95% CI 1.95-52.9). CONCLUSIONS: CTC frequency is a strong, independent predictor of survival in patients with CUP. CTC quantification provides a useful prognostic tool in the management of these patients.

Prostate cancer risk assessment and avoidance of prostate biopsies using fully automatic deep learning in prostate MRI: comparison to PI-RADS and integration with clinical data in nomograms.

OBJECTIVES: Risk calculators (RCs) improve patient selection for prostate biopsy with clinical/demographic information, recently with prostate MRI using the prostate imaging reporting and data system (PI-RADS). Fully-automated deep learning (DL) analyzes MRI data independently, and has been shown to be on par with clinical radiologists, but has yet to be incorporated into RCs. The goal of this study is to re-assess the diagnostic quality of RCs, the impact of replacing PI-RADS with DL predictions, and potential performance gains by adding DL besides PI-RADS. MATERIAL AND METHODS: One thousand six hundred twenty-seven consecutive examinations from 2014 to 2021 were included in this retrospective single-center study, including 517 exams withheld for RC testing. Board-certified radiologists assessed PI-RADS during clinical routine, then systematic and MRI/Ultrasound-fusion biopsies provided histopathological ground truth for significant prostate cancer (sPC). nnUNet-based DL ensembles were trained on biparametric MRI predicting the presence of sPC lesions (UNet-probability) and a PI-RADS-analogous five-point scale (UNet-Likert). Previously published RCs were validated as is; with PI-RADS substituted by UNet-Likert (UNet-Likert-substituted RC); and with both UNet-probability and PI-RADS (UNet-probability-extended RC). Together with a newly fitted RC using clinical data, PI-RADS and UNet-probability, existing RCs were compared by receiver-operating characteristics, calibration, and decision-curve analysis. RESULTS: Diagnostic performance remained stable for UNet-Likert-substituted RCs. DL contained complementary diagnostic information to PI-RADS. The newly-fitted RC spared 49% [252/517] of biopsies while maintaining the negative predictive value (94%), compared to PI-RADS ≥ 4 cut-off which spared 37% [190/517] (p < 0.001). CONCLUSIONS: Incorporating DL as an independent diagnostic marker for RCs can improve patient stratification before biopsy, as there is complementary information in DL features and clinical PI-RADS assessment. CLINICAL RELEVANCE STATEMENT: For patients with positive prostate screening results, a comprehensive diagnostic workup, including prostate MRI, DL analysis, and individual classification using nomograms can identify patients with minimal prostate cancer risk, as they benefit less from the more invasive biopsy procedure. KEY POINTS: The current MRI-based nomograms result in many negative prostate biopsies. The addition of DL to nomograms with clinical data and PI-RADS improves patient stratification before biopsy. Fully automatic DL can be substituted for PI-RADS without sacrificing the quality of nomogram predictions. Prostate nomograms show cancer detection ability comparable to previous validation studies while being suitable for the addition of DL analysis.

Therapeutic drug monitoring of osimertinib in non-small cell lung cancer and short bowel syndrome: A case report.

Short bowel syndrome (SBS) following extensive intestinal resection is often characterized by impaired absorption of orally administered drugs, including tyrosine kinase inhibitors (TKI). We report the case of a patient with EGFR-mutated non-small cell lung carcinoma treated with 80 mg/day of the TKI osimertinib who achieved partial response of the tumour, but was subsequently subjected to a double-barrelled jejunostomy due to ileus. Due to the development of SBS after the bypass surgery, plasma concentrations of osimertinib were monitored using mass spectrometry. The therapeutic drug monitoring confirmed a malabsorption of osimertinib in the patient (108 ng/mL, which is below the 5th percentile of the expected plasma concentration) and was useful to guide adjustments of TKI dosing in order to achieve adequate blood levels (161 ng/mL after increase of the dose to 120 mg/day) in order to maintain tumour control.

Expanding the molecular spectrum of gene fusions in endometrial stromal sarcoma: Novel subunits of the chromatin remodeling complexes PRC2 and NuA4/TIP60 as alternative fusion partners.

Endometrial stromal sarcomas (ESS) are morphologically and molecularly heterogeneous. We report novel gene fusions (EPC1::EED, EPC1::EZH2, ING3::PHF1) identified by targeted RNA sequencing in five cases. The ING3::PHF1-fusion positive ESS presented in a 58-year-old female as extrauterine mesocolonic, ovarian masses, and displayed large, monomorphic ovoid-to-epithelioid cells arranged in solid sheets. The patient remained alive with disease 13 months after surgery. The three ESS with EPC1::EED occurred in the uterine corpus in patients with a median age of 58 years (range 27-62 years). One tumor showed a uniform epithelioid nested morphology, while the other two were composed of monomorphic spindle cells in fascicles with elevated mitotic figures, focal tumor cell necrosis, and lymphovascular invasion. At a median follow-up of 20 months, two patients developed local recurrence, including one with concomitant distant metastasis, while one patient remained free of disease. All three patients were alive at the last follow-up. The EPC1::EZH2-fusion positive ESS presented in a 52-year-old female in the uterus, and displayed uniform spindled cells arranged in short fascicles, with focally elevated mitotic activity but without necrosis. The patient remained free of disease 3 months after surgery. All cases were diffusely positive for CD10; four diffusely express estrogen and progesterone receptors. Our study expands the molecular spectrum of EPC1 and PHF1-related gene fusions in ESS to include additional novel subunits of the PRC2 and/or NuA4/TIP60 complexes. These cases displayed a monomorphic epithelioid or spindled phenotype, spanning low-grade and high-grade cytomorphology, all expressing CD10 and commonly ER and PR, and are prone to local and/or distant spread.

Real-world data for precision cancer medicine-A European perspective.

Leveraging real-world data (RWD) for drug access is necessary to overcome a key challenge of modern precision oncology: tackling numerous low-prevalence oncogenic mutations across cancers. Withholding a potentially active medication in patients with rare mutations for the sake of control chemotherapy or "best" supportive care is neither practicable nor ethically justifiable anymore, particularly as RWD could meanwhile be used instead, according to scientific principles outlined by the US Food and Drug Administration, European Medicines Agency and other stakeholders. However, practical implementation varies, with occasionally opposite recommendations based on the same evidence in different countries. In the face of growing need for precision drugs, more transparency of evaluation, a priori availability of guidance for the academia and industry, as well as a harmonized framework for health technology assessment across the European Union (EU) are imperative. These could in turn trigger infrastructural changes in national and pan-European registries, cancer management guidelines (e.g., frequency of routine radiologic restaging, inclusion of patient-reported outcomes), and the health data space, to ensure conformity with declared standards and facilitate extraction of RWD sets (including patient-level data) suitable for approval and pricing with minimal effort. For an EU-wide unification of precision cancer medicine, collective negotiation of drug supply contracts and funding solidarity would additionally be required to handle the financial burden. According to experience from pivotal European programs, off-label use could potentially also be harmonized across EU-states to accelerate availability of novel drugs, streamline collection of valuable RWD, and mitigate related costs through wider partnerships with pharmaceutical companies.

Artificial intelligence and pathology: From principles to practice and future applications in histomorphology and molecular profiling.

The complexity of diagnostic (surgical) pathology has increased substantially over the last decades with respect to histomorphological and molecular profiling. Pathology has steadily expanded its role in tumor diagnostics and beyond from disease entity identification via prognosis estimation to precision therapy prediction. It is therefore not surprising that pathology is among the disciplines in medicine with high expectations in the application of artificial intelligence (AI) or machine learning approaches given their capabilities to analyze complex data in a quantitative and standardized manner to further enhance scope and precision of diagnostics. While an obvious application is the analysis of histological images, recent applications for the analysis of molecular profiling data from different sources and clinical data support the notion that AI will enhance both histopathology and molecular pathology in the future. At the same time, current literature should not be misunderstood in a way that pathologists will likely be replaced by AI applications in the foreseeable future. Although AI will transform pathology in the coming years, recent studies reporting AI algorithms to diagnose cancer or predict certain molecular properties deal with relatively simple diagnostic problems that fall short of the diagnostic complexity pathologists face in clinical routine. Here, we review the pertinent literature of AI methods and their applications to pathology, and put the current achievements and what can be expected in the future in the context of the requirements for research and routine diagnostics.

Trailblazing precision medicine in Europe: A joint view by Genomic Medicine Sweden and the Centers for Personalized Medicine, ZPM, in Germany.

Over the last decades, rapid technological and scientific advances have led to a merge of molecular sciences and clinical medicine, resulting in a better understanding of disease mechanisms and the development of novel therapies that exploit specific molecular lesions or profiles driving disease. Precision oncology is here used as an example, illustrating the potential of precision/personalized medicine that also holds great promise in other medical fields. Real-world implementation can only be achieved by dedicated healthcare connected centers which amass and build up interdisciplinary expertise reflecting the complexity of precision medicine. Networks of such centers are ideally suited for a nation-wide outreach offering access to precision medicine to patients independent of their place of residence. Two of these multicentric initiatives, Genomic Medicine Sweden (GMS) and the Centers for Personalized Medicine (ZPM) initiative in Germany have teamed up to present and share their views on core concepts, potentials, challenges, and future developments in precision medicine. Together with other initiatives worldwide, GMS and ZPM aim at providing a robust and sustainable framework, covering all components from technology development to clinical trials, ethical and legal aspects as well as involvement of all relevant stakeholders, including patients and policymakers in the field.

Tumour budding-based grading as independent prognostic biomarker in HPV-positive and HPV-negative head and neck cancer.

BACKGROUND: The prognostic significance of tumour budding (TB) and minimal cell nest size (MCNS) was shown in human papillomavirus (HPV)-negative head and neck squamous cell carcinomas (HNSCC). However, the optimisation of cutpoints, the prognostic impact in HPV-positive HNSCC, and the comparison with other histopathological grading systems are insufficiently investigated. METHODS: TB and MCNS were analysed digitally in 1 and 10 high-power fields (HPF) of 331 HPV-positive and HPV-negative cases from TCGA. Optimising the cutpoints a new cellular dissociation grading (CDG) system was defined and compared to the WHO grading and the Brandwein-Gensler (BG) risk model. RESULTS: The two-tiered CDG system based solely on TB yielded optimal prognostic stratification with shortened overall survival for CDG-high cases. Optimal cut-offs were two buds (1 HPF) and six buds (10 HPF), respectively. Analysing MCNS did not add prognostic significance to quantifying TB. CDG was a significant prognostic marker in HPV-negative and HPV-positive tumours and prognostically superior to the WHO and BG systems. High CDG was associated with clinically occult lymph-node metastases. CONCLUSIONS: The most comprehensive study of TB in HNSCC so far confirmed its prognostic impact in HPV-negative tumours and for the first time in HPV-positive tumours. Further studies are warranted to evaluate its applicability for therapy guidance in HNSCC.

Supporting Biomarker-Driven Therapies in Oncology: A Genomic Testing Cost Calculator.

BACKGROUND: Adoption of high-throughput, gene panel-based, next-generation sequencing (NGS) into routine cancer care is widely supported, but hampered by concerns about cost. To inform policies regarding genomic testing strategies, we propose a simple metric, cost per correctly identified patient (CCIP), that compares sequential single-gene testing (SGT) vs. multiplex NGS in different tumor types. MATERIALS AND METHODS: A genomic testing cost calculator was developed based on clinically actionable genomic alterations identified in the European Society for Medical Oncology Scale for Clinical Actionability of molecular Targets. Using sensitivity/specificity data for SGTs (immunohistochemistry, polymerase chain reaction, and fluorescence in situ hybridization) and NGS and marker prevalence, the number needed to predict metric was monetarized to estimate CCIP. RESULTS: At base case, CCIP was lower with NGS than sequential SGT for advanced/metastatic non-squamous non-small cell lung cancer (NSCLC), breast, colorectal, gastric cancers, and cholangiocarcinoma. CCIP with NGS was also favorable for squamous NSCLC, pancreatic, and hepatic cancers, but with overlapping confidence intervals. CCIP favored SGT for prostate cancer. Alternate scenarios using different price estimates for each test showed similar trends, but with incremental changes in the magnitude of difference between NGS and SGT, depending on price estimates for each test. CONCLUSIONS: The cost to correctly identify clinically actionable genomic alterations was lower for NGS than sequential SGT in most cancer types evaluated. Decreasing price estimates for NGS and the rapid expansion of targeted therapies and accompanying biomarkers are anticipated to further support NGS as a preferred diagnostic standard for precision oncology.

The Different Immune Profiles of Normal Colonic Mucosa in Cancer-Free Lynch Syndrome Carriers and Lynch Syndrome Colorectal Cancer Patients.

BACKGROUND & AIMS: Owing to the high load of immunogenic frameshift neoantigens, tumors arising in individuals with Lynch syndrome (LS), the most common inherited colorectal cancer (CRC) syndrome, are characterized by a pronounced immune infiltration. However, the immune status of normal colorectal mucosa in LS is not well characterized. We assessed the immune infiltrate in tumor-distant normal colorectal mucosa from LS CRC patients, sporadic microsatellite-unstable (MSI) and microsatellite-stable (MSS) CRC patients, and cancer-free LS carriers. METHODS: CD3-positive, FOXP3-positive, and CD8-positive T cells were quantified in, respectively, 219, 233, and 201 formalin-fixed paraffin-embedded (FFPE) normal colonic mucosa tissue sections from CRC patients and cancer-free LS carriers and 26, 22, and 19 LS CRCs. CD3-positive T cells were also quantified in an independent cohort of 97 FFPE normal rectal mucosa tissue sections from LS carriers enrolled in the CAPP2 clinical trial. The expression of 770 immune-relevant genes was analyzed in a subset of samples with the use of the NanoString nCounter platform. RESULTS: LS normal mucosa specimens showed significantly elevated CD3-, FOXP3-, and CD8-positive T-cell densities compared with non-LS control specimens. Gene expression profiling and cluster analysis revealed distinct immune profiles in LS carrier mucosa with and without cancer manifestation. Long-term follow-up of LS carriers within the CAPP2 trial found a correlation between mucosal T-cell infiltrate and time to subsequent tumor occurrence. CONCLUSIONS: LS carriers show elevated mucosal T-cell infiltration even in the absence of cancer. The normal mucosa immune profile may be a temporary or permanent tumor risk modifier in LS carriers.