First-in-human study of GFH018, a small molecule inhibitor of transforming growth factor-ß receptor I inhibitor, in patients with advanced solid tumors.

BACKGROUND: Transforming growth factor-ß (TGF-ß) is a cytokine with multiple functions, including cell growth regulation, extracellular matrix production, angiogenesis homeostasis adjustment and et al. TGF-ß pathway activation promotes tumor metastasis/progression and mediates epithelial-mesenchymal transmission suppressing immunosurveillance in advanced tumors. GFH018, a small molecule inhibitor blocking TGF-ß signal transduction, inhibits the progression and/or metastasis of advanced cancers. This first-in-human study evaluated the safety, tolerability, pharmacokinetics (PK), and efficacy of GFH018 monotherapy in patients with advanced solid tumors. METHODS: This phase I, open-label, multicenter study used a modified 3+3 dose escalation and expansion design. Adult patients with advanced solid tumors failing the standard of care were enrolled. Starting at 5 mg, eight dose levels up to 85 mg were evaluated. Patients received GFH018 BID (14d-on/14d-off) starting on the 4th day after a single dose on cycle 1, day 1. Subsequent cycles were defined as 28 days. The study also explored the safety of 85 mg BID 7d-on/7d-off. Adverse events were graded using NCI criteria for adverse events (NCI-CTCAE v5.0). PK was analyzed using a noncompartmental method. Efficacy was evaluated using RECIST 1.1. Blood samples were collected for biomarker analysis. RESULTS: Fifty patients were enrolled and received at least one dose of GFH018. No dose-limiting toxicity occurred, and the maximum tolerated dose was not reached. Forty-three patients (86.0%) had at least one treatment-related adverse event (TRAE), and three patients (6.0%) had ≥ G3 TRAEs. The most common TRAEs (any grade/grade ≥3) were AST increased (18%/0%), proteinuria (14%/2%), anemia (14%/2%), and ALT increased (12%/0%). No significant cardiotoxicity or bleeding was observed. GFH018 PK was linear and dose-independent, with a mean half-life of 2.25-8.60 h from 5 - 85 mg. Nine patients (18.0%) achieved stable disease, and one patient with thymic carcinoma achieved tumor shrinkage, with the maximum target lesion decreased by 18.4%. Serum TGF-ß1 levels were not associated with clinical responses. The comprehensive recommended dose for Phase II was defined as 85 mg BID 14d-on/14d-off. CONCLUSIONS: GFH018 monotherapy presented a favorable safety profile without cardiac toxicity or bleeding. Modest efficacy warrants further studies, including combination strategies. TRIAL REGISTRATION: ClinicalTrial. gov ( https://www. CLINICALTRIALS: gov/ ), NCT05051241. Registered on 2021-09-02.

Molecular Aspects of Mucoepidermoid Carcinoma and Adenoid Cystic Carcinoma of the Salivary Gland.

BACKGROUND: Salivary gland tumors (SGTs) are rare and highly heterogeneous lesions, making diagnosis a challenging activity. In addition, the small number of studies and samples evaluated difficults the determination of prognosis and diagnosis. Despite the solid advances achieved by research, there is still an intense need to investigate biomarkers for diagnosis, prognosis and that explain the evolution and progression of SGTs. METHODS: We performed a comprehensive literature review of the molecular alterations focusing on the most frequent malignant SGTs: mucoepidermoid carcinoma and adenoid cystic carcinoma. RESULTS: Due to the importance of biomarkers in the tumorigenenic process, this review aimed to address the mechanisms involved and to describe molecular and biomarker pathways to better understand some aspects of the pathophysiology of salivary gland tumorigenesis. CONCLUSIONS: Molecular analysis is essential not only to improve the diagnosis and prognosis of the tumors but also to identify novel driver pathways in the precision medicine scenario.

Total metabolic tumor volume on 18F-FDG PET/CT is a game-changer for patients with metastatic lung cancer treated with immunotherapy.

PURPOSE: Because of atypical response imaging patterns in patients with metastatic non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICPIs), new biomarkers are needed for a better monitoring of treatment efficacy. The aim of this prospective study was to evaluate the prognostic value of volume-derived positron-emission tomography (PET) parameters on baseline and follow-up 18F-fluoro-deoxy-glucose PET (18F-FDG-PET) scans and compare it with the conventional PET Response Criteria in Solid Tumors (PERCIST). METHODS: Patients with metastatic NSCLC were included in two different single-center prospective trials. 18F-FDG-PET studies were performed before the start of immunotherapy (PETbaseline), after 6-8 weeks (PETinterim1) and after 12-16 weeks (PETinterim2) of treatment, using PERCIST criteria for tumor response assessment. Different metabolic parameters were evaluated: absolute values of maximum standardized uptake value (SUVmax) of the most intense lesion, total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), but also their percentage changes between PET studies (ΔSUVmax, ΔTMTV and ΔTLG). The median follow-up of patients was 31 (7.3-31.8) months. Prognostic values and optimal thresholds of PET parameters were estimated by ROC (Receiver Operating Characteristic) curve analysis of 12-month overall survival (12M-OS) and 6-month progression-free survival (6M-PFS). Tumor progression needed to be confirmed by a multidisciplinary tumor board, considering atypical response patterns on imaging. RESULTS: 110 patients were prospectively included. On PETbaseline, TMTV was predictive of 12M-OS [AUC (Area Under Curve) =0.64; 95% CI: 0.61 to 0.66] whereas SUVmax and TLG were not. On PETinterim1 and PETinterim2, all metabolic parameters were predictive for 12M-OS and 6M-PFS, the residual TMTV on PETinterim1 (TMTV1) being the strongest prognostic biomarker (AUC=0.83 and 0.82; 95% CI: 0.74 to 0.91, for 12M-OS and 6M-PFS, respectively). Using the optimal threshold by ROC curve to classify patients into three TMTV1 subgroups (0 cm3; 0-57 cm3; >57 cm3), TMTV1 prognostic stratification was independent of PERCIST criteria on both PFS and OS, and significantly outperformed them. Subgroup analysis demonstrated that TMTV1 remained a strong prognostic biomarker of 12M-OS for non-responding patients (p=0.0003) according to PERCIST criteria. In the specific group of patients with PERCIST progression on PETinterim1, low residual tumor volume (<57 cm3) was still associated with a very favorable patients' outcome (6M-PFS=73%; 24M-OS=55%). CONCLUSION: The absolute value of residual metabolic tumor volume, assessed 6-8 weeks after the start of ICPI, is an optimal and independent prognostic measure, exceeding and complementing conventional PERCIST criteria. Oncologists should consider it in patients with first tumor progression according to PERCIST criteria, as it helps identify patients who benefit from continued treatment. TRIAL REGISTRATION NUMBER: 2018-A02116-49; NCT03584334.

Tumor-agnostic transcriptome-based classifier identifies spatial infiltration patterns of CD8+T cells in the tumor microenvironment and predicts clinical outcome in early-phase and late-phase clinical trials.

BACKGROUND: The immune status of a patient's tumor microenvironment (TME) may guide therapeutic interventions with cancer immunotherapy and help identify potential resistance mechanisms. Currently, patients' immune status is mostly classified based on CD8+tumor-infiltrating lymphocytes. An unmet need exists for comparable and reliable precision immunophenotyping tools that would facilitate clinical treatment-relevant decision-making and the understanding of how to overcome resistance mechanisms. METHODS: We systematically analyzed the CD8 immunophenotype of 2023 patients from 14 phase I-III clinical trials using immunohistochemistry (IHC) and additionally profiled gene expression by RNA-sequencing (RNA-seq). CD8 immunophenotypes were classified by pathologists into CD8-desert, CD8-excluded or CD8-inflamed tumors using CD8 IHC staining in epithelial and stromal areas of the tumor. Using regularized logistic regression, we developed an RNA-seq-based classifier as a surrogate to the IHC-based spatial classification of CD8+tumor-infiltrating lymphocytes in the TME. RESULTS: The CD8 immunophenotype and associated gene expression patterns varied across indications as well as across primary and metastatic lesions. Melanoma and kidney cancers were among the strongest inflamed indications, while CD8-desert phenotypes were most abundant in liver metastases across all tumor types. A good correspondence between the transcriptome and the IHC-based evaluation enabled us to develop a 92-gene classifier that accurately predicted the IHC-based CD8 immunophenotype in primary and metastatic samples (area under the curve inflamed=0.846; excluded=0.712; desert=0.855). The newly developed classifier was prognostic in The Cancer Genome Atlas (TCGA) data and predictive in lung cancer: patients with predicted CD8-inflamed tumors showed prolonged overall survival (OS) versus patients with CD8-desert tumors (HR 0.88; 95% CI 0.80 to 0.97) across TCGA, and longer OS on immune checkpoint inhibitor administration (phase III OAK study) in non-small-cell lung cancer (HR 0.75; 95% CI 0.58 to 0.97). CONCLUSIONS: We provide a new precision immunophenotyping tool based on gene expression that reflects the spatial infiltration patterns of CD8+ lymphocytes in tumors. The classifier enables multiplex analyses and is easy to apply for retrospective, reverse translation approaches as well as for prospective patient enrichment to optimize the response to cancer immunotherapy.

Abnormal expression of Krüppel-like transcription factors and their potential values in lung cancer.

Lung cancer still is one of the most common malignancy tumors in the world. However, the mechanisms of its occurrence and development have not been fully elucidated. Zinc finger protein family (ZNFs) is the largest transcription factor family in human genome. Recently, the more and more basic and clinical evidences have confirmed that ZNFs/Krüppel-like factors (KLFs) refer to a group of conserved zinc finger-containing transcription factors that are involved in lung cancer progression, with the functions of promotion, inhibition, dual roles and unknown classifications. Based on the recent literature, some of the oncogenic KLFs are promising molecular biomarkers for diagnosis, prognosis or therapeutic targets of lung cancer. Interestingly, a novel computational approach has been proposed by using machine learning on features calculated from primary sequences, the XGBoost-based model with accuracy of 96.4 % is efficient in identifying KLF proteins. This paper reviews the recent some progresses of the oncogenic KLFs with their potential values for diagnosis, prognosis and molecular target in lung cancer.

Relevance of blood tumor markers in inpatients with significant involuntary weight loss and elevated levels of inflammation biomarkers.

PURPOSE: To assess the diagnostic performance of a panel of standard tumor markers (TMs) in patients hospitalized with significant involuntary weight loss (IWL) and elevated levels of inflammation biomarkers, and a combination of the TM panel and the finding of the computed tomography (CT) scan. METHODS: We conducted a retrospective study in the internal medicine department at Amiens-Picardie University Medical Center (Amiens, France) between January 1st, 2015, and November 1st, 2021. The inclusion criteria were age 18 or over, significant IWL (≥ 5 kg over 6 months), elevated inflammation biomarkers (e.g. C-reactive protein), and assay data on two or more standard TMs (carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 19 - 9, CA 15 - 3, CA 125, neuron-specific enolase (NSE), alpha-fetoprotein (AFP), calcitonin, and prostate-specific antigen (PSA)). The result of each TM assay was interpreted qualitatively (as positive or negative), according to our central laboratory's usual thresholds. RESULTS: Cancer was diagnosed in 50 (37.0%) of the 135 patients included. Positivity for one or more TMs had a positive predictive value (PPV) of 0.55 [0.43-0.66], and a negative predictive value (NPV) of 0.84 [0.75-0.93] for cancer diagnosis. When combined with the presence of suspicious CT findings (e.g. a mass, enlarged lymph nodes and/or effusion), positivity for one or more TMs had a PPV of 0.92 [0.08-0.30]. In the absence of suspicious CT findings, a fully negative TM panel had an NPV of 0.96 [0.89-1.00]. CONCLUSION: A negative TM panel argues against the presence of a cancer, especially in the absence of suspicious CT findings.

Fiber-optic immunosensor based on a Fabry-Perot interferometer for single-molecule detection of biomarkers.

Immunosensors capable of ultralow-concentration and single-molecule detection of biomarkers are garnering attention for the early diagnosis of cancer. Herein, a fiber-optic Fabry-Perot interferometer (FPI)-based immunosensor was used for the first time for single-molecule detection of progastrin-releasing peptide (ProGRP). The cascaded FPI structure of the immunosensor introduces a high-order harmonic Vernier effect (HVE). A piece of a side-polished D-shaped hollow-core photonic crystal fiber (HCPCF) was used as a sensing FPI, on which the biomarker was deposited to detect ProGRP. Compared with traditional FPIs with open-cavity structures, this structure provided a larger contact area and improved the sensitivity of the immunosensor. The polished side surface of the D-shaped HCPCF was modified using a gold nanoparticle-graphene oxide (AuNP@GO) nanointerface to enhance refractive index (RI) modulation via antigen-antibody binding and achieve selective energy enhancement of the binding site. The antigen binding changes the RI of the D-shaped HCPCF and the effective RI of the transmitted light in the sensing FPI, thereby changing the spectrum of the immunosensor. Experimental results showed that the high-order HVE and AuNP@GO nanointerface considerably improved the immunosensor sensitivity, exhibiting a liquid RI sensitivity of 583,000 nm/RIU. After functionalization with an anti-ProGRP antibody, the limit of detection of the immunosensor for ProGRP reached 17.1 ag/mL; moreover, the immunosensor could perform detection at the single-molecule level. The proposed novel immunosensor overcomes the sensitivity limitations of optical devices and achieves single-molecule detection of a protein.

Digital spatial proteomic profiling reveals immune checkpoints as biomarkers in lymphoid aggregates and tumor microenvironment of desmoplastic melanoma.

BACKGROUND: Desmoplastic melanoma (DM) is a rare melanoma subtype characterized by dense fibrous stroma, a propensity for local recurrence, and a high response rate to programmed cell death protein 1 (PD-1) blockade. Occult sentinel lymph node positivity is significantly lower in both pure and mixed DM than in conventional melanoma, underscoring the need for better prognostic biomarkers to inform therapeutic strategies. METHODS: We assembled a tissue microarray comprising various cores of tumor, stroma, and lymphoid aggregates from 45 patients with histologically confirmed DM diagnosed between 1989 and 2018. Using a panel of 62 validated immune-oncology markers, we performed digital spatial profiling using the NanoString GeoMx platform and quantified expression in three tissue compartments defined by fluorescence colocalization (tumor (S100+/PMEL+/SYTO+), leukocytes (CD45+/SYTO+), and non-immune stroma (S100-/PMEL-/CD45-/SYTO+)). RESULTS: We observed higher expression of immune checkpoints (lymphocyte-activation gene 3 [LAG-3] and cytotoxic T-lymphocyte associated protein-4 [CTLA-4]) and cancer-associated fibroblast (CAF) markers (smooth muscle actin (SMA)) in the tumor compartments of pure DMs than mixed DMs. When comparing lymphoid aggregates (LA) to non-LA tumor cores, LAs were more enriched with CD20+B cells, but non-LA intratumoral leukocytes were more enriched with macrophage/monocytic markers (CD163, CD68, CD14) and had higher LAG-3 and CTLA-4 expression levels. Higher intratumoral PD-1 and LA-based LAG-3 expression appear to be associated with worse survival. CONCLUSIONS: Our proteomic analysis reveals an intra-tumoral population of SMA+CAFs enriched in pure DM. Additionally, increased expressions of immune checkpoints (LAG-3 and PD-1) in LA and within tumor were associated with poorer prognosis. These findings might have therapeutic implications and help guide treatment selection in addition to informing potential prognostic significance.

Longitudinal Tumor-informed Circulating Tumor DNA Status Predicts Disease Upstaging and Poor Prognosis for Patients Undergoing Radical Cystectomy.

BACKGROUND AND OBJECTIVE: Decision-making on the use of neoadjuvant and adjuvant treatment for patients with bladder cancer undergoing radical cystectomy (RC) currently depends on assessment of clinical and pathological features, which lack sensitivity. Circulating tumor DNA (ctDNA) has emerged as a possible novel prognostic biomarker in the field. Our aim was to assess whether ctDNA status before RC is predictive of pathological and oncological outcomes. We also evaluated the dynamic changes in ctDNA status after RC in relation to recurrence-free survival (RFS). METHODS: We analyzed data for patients who underwent RC during 2021-2023 for whom prospective tumor-informed ctDNA analyses were conducted before and after RC. RFS was evaluated using the Kaplan-Meier method. Predictors for disease recurrence were assessed using Cox proportional-hazards models. Pathological outcomes associated with detectable ctDNA before RC were assessed in univariable and multivariable regression analyses. KEY FINDINGS AND LIMITATIONS: We included 112 patients in the analysis. Median follow-up was 8 mo (interquartile range 4-13). ctDNA was detected before RC in 59 patients (53%) and was associated with poor RFS (log-rank p < 0.0001). Detectable ctDNA before RC was associated with poor outcomes regardless of clinical stage (

Modified FOLFOX6 plus bevacizumab with and without nivolumab for first-line treatment of metastatic colorectal cancer: phase 2 results from the CheckMate 9X8 randomized clinical trial.

BACKGROUND: Standard first-line therapies for metastatic colorectal cancer (mCRC) include fluoropyrimidine-containing regimens with oxaliplatin and/or irinotecan and a biologic agent. Immunotherapy may enhance antitumor activity in combination with standard therapies in patients with mCRC. Here, we present phase 2 results of nivolumab plus standard-of-care therapy (SOC; 5-fluorouracil/leucovorin/oxaliplatin/bevacizumab) versus SOC in the first-line treatment of patients with mCRC (CheckMate 9X8). METHODS: CheckMate 9X8 was a multicenter, open-label, randomized, phase 2/3 trial. Eligible patients were at least 18 years of age with unresectable mCRC and no prior chemotherapy for metastatic disease. Patients were randomized 2:1 to receive nivolumab 240 mg plus SOC or SOC alone every 2 weeks. The primary endpoint was progression-free survival (PFS) by blinded independent central review (BICR) per Response Evaluation Criteria in Solid Tumors V.1.1. Secondary endpoints included PFS by investigator assessment; objective response rate (ORR), disease control rate, duration of response, and time to response, all by BICR and investigator assessments; overall survival; and safety. Preplanned exploratory biomarker analyses were also performed. RESULTS: From February 2018 through April 2019, 310 patients were enrolled, of which 195 patients were randomized to nivolumab plus SOC (n=127) or SOC (n=68). At 21.5-month minimum follow-up, PFS with nivolumab plus SOC versus SOC did not meet the prespecified threshold for statistical significance; median PFS by BICR was 11.9 months in both arms (HR, 0.81 (95% CI, 0.53 to 1.23); p=0.30). Higher PFS rates after 12 months (18 months: 28% vs 9%), higher ORR (60% vs 46%), and durable responses (median 12.9 vs 9.3 months) were observed with nivolumab plus SOC versus SOC. Grade 3-4 treatment-related adverse events were reported in 75% versus 48% of patients; no new safety signals were identified. CONCLUSIONS: The CheckMate 9X8 trial investigating first-line nivolumab plus SOC versus SOC in patients with mCRC did not meet its primary endpoint of PFS by BICR. Nivolumab plus SOC showed numerically higher PFS rates after 12 months, a higher response rate, and more durable responses compared with SOC alone, with acceptable safety. Further investigation to identify subgroups of patients with mCRC that may benefit from nivolumab plus SOC versus SOC in the first-line setting is warranted. TRIAL REGISTRATION NUMBER: NCT03414983.

Cancer-oocyte SAS1B protein is expressed at the cell surface of multiple solid tumors and targeted with antibody-drug conjugates.

BACKGROUND: Sperm acrosomal SLLP1 binding (SAS1B) protein is found in oocytes, which is necessary for sperm-oocyte interaction, and also in uterine and pancreatic cancers. Anti-SAS1B antibody-drug conjugates (ADCs) arrested growth in these cancers. However, SAS1B expression in cancers and normal tissues has not been characterized. We hypothesized that SAS1B is expressed on the surface of other common solid cancer cells, but not on normal tissue cells, and might be selectively targeted therapeutically. METHODS: SAS1B expression in human normal and cancer tissues was determined by immunohistochemistry, and complementary DNA (cDNA) libraries were employed to PCR amplify human SAS1B and its transcripts. Monoclonal antibodies (mAbs) to human SAS1B were generated using mouse hybridomas. SAS1B deletion constructs were developed to map SAS1B's epitope, enabling the creation of a blocking peptide. Indirect immunofluorescence (IIF) of human transfected normal and cancer cells was performed to assess SAS1B expression. SAS1B intracellular versus surface expression in normal and tumor tissues was evaluated by flow cytometry after staining with anti-SAS1B mAb, with specificity confirmed with the blocking peptide. Human cancer lines were treated with increasing mAb and ADC concentrations. ATP was quantitated as a measure of cell viability. RESULTS: SAS1B expression was identified in a subset of human cancers and the cytoplasm of pancreatic islet cells. Two new SAS1B splice variants were deduced. Monoclonal antibodies were generated to SAS1B splice variant A. The epitope for mAbs SB2 and SB5 is between SAS1B amino acids 32-39. IIF demonstrated intracellular SAS1B expression in transfected kidney cells and on the cell surface of squamous cell lung carcinoma. Flow cytometry demonstrated intracellular SAS1B expression in all tumors and some normal cells. However, surface expression of SAS1B was identified only on cancer cells. SB2 ADC mediated dose-dependent cytotoxic killing of multiple human cancer lines. CONCLUSION: SAS1B is a novel cancer-oocyte antigen with cell surface expression restricted to cancer cells. In vitro, it is an effective target for antibody-mediated cancer cell lysis. These findings support further exploration of SAS1B as a potential therapeutic cancer target in multiple human cancers, either with ADC or as a chimeric antigen receptor-T (CAR-T) cell target.

Harmonization of tumor mutation burden testing with comprehensive genomic profiling assays: an IQN Path initiative.

BACKGROUND: Although conflicting results emerged from different studies, the tumor mutational burden (TMB) appears as one of most reliable biomarkers of sensitivity to immune checkpoint inhibitors. Several laboratories are reporting TMB values when performing comprehensive genomic profiling (CGP) without providing a clinical interpretation, due to the lack of validated cut-off values. The International Quality Network for Pathology launched an initiative to harmonize TMB testing with CGP assay and favor the clinical implementation of this biomarker. METHODS: TMB evaluation was performed with three commercially available CGP panels, TruSight Oncology 500 (TSO500), Oncomine Comprehensive Plus Assay (OCA) and QIAseq Multimodal Panel (QIA), versus the reference assay FoundationOne CDx (F1CDx). Archived clinical samples derived from 60 patients with non-small cell lung cancer were used for TMB assessment. Adjusted cut-off values for each panel were calculated. RESULTS: Testing was successful for 91.7%, 100%, 96.7% and 100% of cases using F1CDx, TSO500, OCA and QIA, respectively. The matrix comparison analysis, between the F1CDx and CGP assays, showed a linear correlation for all three panels, with a higher correlation between F1CDx and TSO500 (rho=0.88) than in the other two comparisons (rho=0.77 for QIA; 0.72 for OCA). The TSO500 showed the best area under the curve (AUC, value 0.96), with a statistically significant difference when compared with the AUC of OCA (0.83, p value=0.01) and QIA (0.88, p value=0.028). The Youden Index calculation allowed us to extrapolate TMB cut-offs of the different panels corresponding to the 10 mutations/megabase (muts/Mb) cut-off of F1CDx: 10.19, 10.4 and 12.37 muts/Mb for TSO500, OCA and QIA, respectively. Using these values, we calculated the relative accuracy measures for the three panels. TSO500 showed 86% specificity and 96% sensitivity, while OCA and QIA had lower yet similar values of specificity and sensitivity (73% and 88%, respectively). CONCLUSION: This study estimated TMB cut-off values for commercially available CGP panels. The results showed a good performance of all panels on clinical samples and the calculated cut-offs support better accuracy measures for TSO500. The validated cut-off values can drive clinical interpretation of TMB testing in clinical research and clinical practice.

Prognostic and predictive value of angiogenesis-associated serum proteins for immunotherapy in esophageal cancer.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have significantly improved patient survival in multiple cancers. However, therapy response in esophageal cancer is limited to subgroups of patients and clinically useful predictive biomarkers are lacking. METHODS: We collected a series of plasma samples from 91 patients with esophageal cancer before and after ICI treatment. The Olink Immuno-Oncology panel (92 proteins) with proximity extension assays was used to detect the dynamic changes in plasma and potential biomarkers associated with treatment outcomes. We screened all survival-related proteins and established a risk score model to better predict the prognosis and treatment response in patients with esophageal cancer immunotherapy. RESULTS: We found that 47 out of 92 quantified proteins had significant changes in plasma levels during ICI treatment (p<0.050), and these changed proteins were involved in immune-related reactions, such as intercellular adhesion and T-cell activation. Notably, the baseline levels of three angiogenesis-related proteins (IL-8, TIE2, and HGF) were significantly associated with the survival outcomes of patients treated with ICIs (p<0.050). According to these prognostic proteins, we established an angiogenesis-related risk score, which could be a superior biomarker for ICI response prediction. In addition, antiangiogenic therapy combined with ICIs significantly improved overall survival compared with ICI monotherapy (p=0.044). CONCLUSIONS: An angiogenesis-related risk score based on three proteins (IL-8, TIE2, and HGF) could predict ICI response and prognosis in patients with esophageal cancer, which warrants verification in the future. Our study highlights the potential application of combining ICIs and antiangiogenic therapy and supports Olink plasma protein sequencing as a liquid biopsy method for biomarker exploration.

Multiomic molecular characterization of the response to combination immunotherapy in MSS/pMMR metastatic colorectal cancer.

BACKGROUND: Immune checkpoint inhibitor (ICI) combinations represent an emerging treatment strategies in cancer. However, their efficacy in microsatellite stable (MSS) or mismatch repair-proficient (pMMR) colorectal cancer (CRC) is variable. Here, a multiomic characterization was performed to identify predictive biomarkers associated with patient response to ICI combinations in MSS/pMMR CRC for the further development of ICI combinations. METHODS: Whole-exome sequencing, RNA sequencing, and multiplex fluorescence immunohistochemistry of tumors from patients with MSS/pMMR CRC, who received regorafenib plus nivolumab (REGONIVO) or TAS-116 plus nivolumab (TASNIVO) in clinical trials were conducted. Twenty-two and 23 patients without prior ICI from the REGONIVO and TASNIVO trials were included in this study. A biomarker analysis was performed using samples from each of these studies. RESULTS: The epithelial-mesenchymal transition pathway and genes related to cancer-associated fibroblasts were upregulated in the REGONIVO responder group, and the G2M checkpoint pathway was upregulated in the TASNIVO responder group. The MYC pathway was upregulated in the REGONIVO non-responder group. Consensus molecular subtype 4 was significantly associated with response (p=0.035) and longer progression-free survival (p=0.006) in the REGONIVO trial. CD8+ T cells, regulatory T cells, and M2 macrophages density was significantly higher in the REGONIVO trial responders than in non-responders. Mutations in the POLE gene and patient response were significantly associated in the TASNIVO trial; however, the frequencies of other mutations or tumor mutational burden were not significantly different between responders and non-responders in either trial. CONCLUSIONS: We identified molecular features associated with the response to the REGONIVO and TASNIVO, particularly those related to tumor microenvironmental factors. These findings are likely to contribute to the development of biomarkers to predict treatment efficacy for MSS/pMMR CRC and future immunotherapy combinations for treatment.

Age-related phenotypes in breast cancer: A population-based study.

Breast cancer in young (<40 years) is associated with a higher frequency of aggressive tumor types and poor prognosis. It remains unclear if there is an underlying age-related biology that contributes to the unfavorable outcome. We aim to investigate the relationship between age and breast cancer biology, with emphasis on proliferation. Clinico-pathologic information, immunohistochemical markers and follow-up data were obtained for all patients aged <50 (Bergen cohort-1; n = 355, not part of a breast screening program) and compared to previously obtained information on patients aged 50 to 69 years (Bergen cohort-2; n = 540), who participated in the Norwegian Breast Cancer Screening Program. Young breast cancer patients presented more aggressive tumor features such as hormone receptor negativity, HER2 positivity, lymph-node metastasis, the HER2-enriched and triple-negative subtypes and shorter survival. Age <40 was significantly associated with higher proliferation (by Ki67). Ki67 showed weaker prognostic value in young patients. We point to aggressive phenotypes and increased tumor cell proliferation in breast cancer of the young. Hence, tumors of young breast cancer patients may present unique biological features, also when accounting for screen/interval differences, that may open for new clinical opportunities, stratifying treatment by age.

Depth of invasion of oral squamous cell carcinoma in Nos2-knockout mice correlated to alterations in systemic inflammatory markers following 4NQO treatment.

BACKGROUND: Peripheral blood analysis is a non-invasive and low-cost technique of prognostic value for several diseases, including oral cancer. Considering the role of inducible nitric oxide synthase in tumor-associated inflammation, this study purposed to evaluate the influence of this enzyme on peripheral blood parameters and systemic inflammatory biomarkers during murine oral carcinogenesis. METHODS: A 50 µg/mL solution of 4-nitroquinoleine-N-oxide was provided to 15 C57BL/6J (Nos2+/+ ) and 16 B6.129P2-Nos2tm1Lau /J (Nos2-/- ) for 16 weeks. Animals were followed for 8 weeks after treatment. Blood samples and tongues were collected for hematological and histopathological analyses. Red blood cells, white blood cells, and platelet cell parameters were analyzed. The neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and the systemic immune-inflammation index were also calculated. The depth of invasion of all carcinomas was measured. RESULTS: Differences were found in several blood parameters. The depth of invasion in Nos2-/- was lower than in Nos2+/+ (p = 0.009), and strong correlations were found between depth of invasion and neutrophil count (ρ = -0.68, p = 0.017), lymphocyte count (ρ = 0.72, p = 0.011), neutrophil-to-lymphocyte ratio (ρ = -0.65, p = 0.025), platelet-to-lymphocyte ratio (ρ = -0.73, p = 0.013), and systemic immune-inflammation index (ρ = -0.67, p = 0.037) in Nos2-/- mice. CONCLUSION: Inducible nitric oxide synthase seems to have an important role in OSCC invasion and progression, which might be associated to alterations in immune-inflammatory cell dynamics evidenced by peripheral blood and systemic inflammatory biomarkers.

H3K27ac-activated LncRNA NUTM2A-AS1 Facilitates the Progression of Colorectal Cancer Cells via MicroRNA-126-5p/FAM3C Axis.

OBJECTIVE: Long non-coding RNAs (lncRNAs) are of great importance in the process of colorectal cancer (CRC) tumorigenesis and progression. However, the functions and underlying molecular mechanisms of the majority of lncRNAs in CRC still lack clarity. METHODS: A Quantitative real-time polymerase chain reaction (qRT-PCR) was employed to detect lncRNA NUTM2A-AS1 expression in CRC cell lines. Cell counting kit 8 (CCK-8) assay and flow cytometry were used to examine the biological functions of lncRNA NUTM2A-AS1 in the proliferation and apoptosis of CRC cells. RT-qPCR and western blot were implemented for the detection of cell proliferation-, apoptosis-related proteins, and FAM3C. Bioinformatics analysis and dual- luciferase reporter assays were utilized to identify the mutual regulatory mechanism of ceRNAs. RESULTS: lncRNA NUTM2A-AS1 notably elevated in CRC cell lines and the silencing of NUTM2A- AS1 declined proliferation and facilitated apoptosis. Mechanistically, NUTM2A-AS1 was transcriptionally activated by histone H3 on lysine 27 acetylation (H3K27ac) enriched at its promoter region, and NUTM2A-AS1 acted as a sponge for miR-126-5p, leading to the upregulation of FAM3C expression in CRC cell lines. CONCLUSION: Our research proposed NUTM2A-AS1 as an oncogenic lncRNA that facilitates CRC malignancy by upregulating FAM3C expression, which might provide new insight and a promising therapeutic target for the diagnosis and treatment of CRC.

Understanding the Landscape of Clinically Available Molecular Testing.

Over the past three decades, the landscape of clinically available molecular tests has evolved due to advancements in basic science cancer research and the subsequent utilization of this knowledge to develop DNA, RNA, and protein-based molecular assays for oncology that can be employed for routine clinical use in diagnostics laboratories. Molecular testing of tumors is revealing gaps in previous histopathologic classification systems and opportunities for new, personalized treatment paradigms. Awareness of validated molecular assay options and their general advantages and limitations is crucial for oncology care providers to ensure the optimal test(s) are selected for each patient's circumstances.

Inflamed immune phenotype predicts favorable clinical outcomes of immune checkpoint inhibitor therapy across multiple cancer types.

BACKGROUND: The inflamed immune phenotype (IIP), defined by enrichment of tumor-infiltrating lymphocytes (TILs) within intratumoral areas, is a promising tumor-agnostic biomarker of response to immune checkpoint inhibitor (ICI) therapy. However, it is challenging to define the IIP in an objective and reproducible manner during manual histopathologic examination. Here, we investigate artificial intelligence (AI)-based immune phenotypes capable of predicting ICI clinical outcomes in multiple solid tumor types. METHODS: Lunit SCOPE IO is a deep learning model which determines the immune phenotype of the tumor microenvironment based on TIL analysis. We evaluated the correlation between the IIP and ICI treatment outcomes in terms of objective response rates (ORR), progression-free survival (PFS), and overall survival (OS) in a cohort of 1,806 ICI-treated patients representing over 27 solid tumor types retrospectively collected from multiple institutions. RESULTS: We observed an overall IIP prevalence of 35.2% and significantly more favorable ORRs (26.3% vs 15.8%), PFS (median 5.3 vs 3.1 months, HR 0.68, 95% CI 0.61 to 0.76), and OS (median 25.3 vs 13.6 months, HR 0.66, 95% CI 0.57 to 0.75) after ICI therapy in IIP compared with non-IIP patients, respectively (p<0.001 for all comparisons). On subgroup analysis, the IIP was generally prognostic of favorable PFS across major patient subgroups, with the exception of the microsatellite unstable/mismatch repair deficient subgroup. CONCLUSION: The AI-based IIP may represent a practical, affordable, clinically actionable, and tumor-agnostic biomarker prognostic of ICI therapy response across diverse tumor types.

Machine learning analysis of pathological images to predict 1-year progression-free survival of immunotherapy in patients with small-cell lung cancer.

BACKGROUND: In small-cell lung cancer (SCLC), the tumor immune microenvironment (TIME) could be a promising biomarker for immunotherapy, but objectively evaluating TIME remains challenging. Hence, we aimed to develop a predictive biomarker of immunotherapy efficacy through a machine learning analysis of the TIME. METHODS: We conducted a biomarker analysis in a prospective study of patients with extensive-stage SCLC who received chemoimmunotherapy as the first-line treatment. We trained a model to predict 1-year progression-free survival (PFS) using pathological images (H&E, programmed cell death-ligand 1 (PD-L1), and double immunohistochemical assay (cluster of differentiation 8 (CD8) and forkhead box P3 (FoxP3)) and patient information. The primary outcome was the mean area under the curve (AUC) of machine learning models in predicting the 1-year PFS. RESULTS: We analyzed 100,544 patches of pathological images from 78 patients. The mean AUC values of patient information, pathological image, and combined models were 0.789 (range 0.571-0.982), 0.782 (range 0.750-0.911), and 0.868 (range 0.786-0.929), respectively. The PFS was longer in the high efficacy group than in the low efficacy group in all three models (patient information model, HR 0.468, 95% CI 0.287 to 0.762; pathological image model, HR 0.334, 95% CI 0.117 to 0.628; combined model, HR 0.353, 95% CI 0.195 to 0.637). The machine learning analysis of the TIME had better accuracy than the human count evaluations (AUC of human count, CD8-positive lymphocyte: 0.681, FoxP3-positive lymphocytes: 0.626, PD-L1 score: 0.567). CONCLUSIONS: The spatial analysis of the TIME using machine learning predicted the immunotherapy efficacy in patients with SCLC, thus supporting its role as an immunotherapy biomarker.