ABSTRACT
BACKGROUND: Immune checkpoint inhibitor (ICI) therapy has been used in various tumors. The biomarkers predictive of a response to ICI treatment remain unclear, and additional and combined biomarkers are urgently needed. Secreted factors related to the tumor microenvironment (TME) have been evaluated to identify novel noninvasive predictive biomarkers. METHODS: We analyzed 85 patients undergoing ICI therapy as the primary cohort. The associations between ICI response and all biomarkers were evaluated. A prediction model and a nomogram were developed and validated based on the above factors. RESULTS: Seventy-seven patients were enrolled in the validation cohort. In the primary cohort, the baseline serum levels of H3Cit, IL-8 and CRP were significantly higher in nonresponder patients. A model based on these three factors was developed, and the "risk score" of an ICI response was calculated with the formula: "risk score" = 3.4591×H3Cit + 2.5808×IL8 + 2.0045 ×CRP- 11.3844. The cutoff point of the "risk score" was 0.528, and patients with a "risk score" lower than 0.528 were more likely to benefit from ICI treatment (AUC: 0.937, 95% CI: 0.886-0.988, with sensitivity 80.60%, specificity 91.40%). The AUC was 0.719 (95% CI: 0.600-0.837, P = 0.001), with a sensitivity of 70.00% and specificity of 65.20% in the validation cohort. CONCLUSIONS: A model incorporating H3Cit, IL-8 and CRP has an excellent prediction ability for ICI response; thus, patients with a lower "risk score" selectively benefit from ICI treatment, which may have significant clinical implications for the early detection of an ICI response.
ABSTRACT
BACKGROUND: With the combination therapy of PD-1/PD-L1 antibody and antiangiogenic drugs used widely in clinic, a novel method to estimate the prognosis of patients is needed. We aimed to develop a nomogram to examine prognosis of anti-PD-1/PD-L1 antibody plus bevacizumab in non-small cell lung cancer (NSCLC) patients. METHODS: We developed a nomogram using the cohort involving 204 NSCLC patients who treated with immunotherapy and anti-angiogenesis therapy. The nomogram was validated under the same conditions in another cohort with 69 patients. Prognostic factors were analyzed by Cox regression analysis. The nomogram was internally validated using bootstrap resampling and then externally validated. Performance was assessed using concordance index, calibration curve and decision curve analysis. Clinical utility was evaluated using receiver operation characteristic curve. RESULTS: Pleural metastasis (P = 0.001, HR = 2.980, 95%CI 1.521-5.837), ANC (P < 0.001, HR = 5.139, 95%CI 2.081-12.691), ALC (P = 0.010, HR = 0.331, 95%CI 0.142-0.771), B cells (P = 0.005, HR = 0.329, 95%CI 0.151-0.714), Treg cells (P = 0.002, HR = 2.934, 95%CI 1.478-5.826) were independent prognostic factors. The calibration curves showed good consistency and the C-index of nomogram were 0.808, 0.741 in training and external validation cohort, respectively. The area under the curve (AUC) in receiver operation characteristic curves (ROC) are 0.833 (P < 0.001) and 0.908 (P < 0.001), respectively. CONCLUSION: We build an accurate and convenient nomogram to predict long-time overall survival (OS) of NSCLC patients treated with PD-1/PD-L1 antibody and antiangiogenic drugs and validated this nomogram. The nomogram might be helpful to clinicians to estimate long-time OS of NSCLC patients treated with PD-1/PD-L1 antibody and antiangiogenic drugs.
ABSTRACT
Background: Colorectal signet-ring cell carcinoma (SRCC) is a rare subtype of malignant adenocarcinoma, accounting for approximately 1 % of colorectal cancer (CRC) cases. Its biomarkers and molecular characteristics remain controversial, and there are no specific therapeutic targets or strategies for its clinical treatment. Methods: A retrospective study was conducted between January 2010 and December 2021. 1058 colorectal cancer cases from the Sun Yat-sen University Cancer Center and 489 cases from the Tumor Genome Atlas Project were included in the analysis, of which 64 were SRCC. Data extraction included patient demographics, blood types and risk factors, including clinical variables and genomics (either a 19-gene panel NGS or 1021-gene panel NGS). Univariate analyses were performed to identify factors significantly associated with overall survival. Results: The blood groups of 27 (42.2 %), 18 (28.1 %), 12 (18.8 %), and seven (10.9 %) patients were classified as O, A, B, and AB, respectively. We found that O was a unique blood group characterized by a low frequency of KRAS mutations, a high frequency of heterozygosity at each HLA class I locus, and a high tumor mutational burden (TMB). Patients in blood group A with high-frequency KRAS mutations and those in blood group B with anemia and metabolic abnormalities required targeted treatment. Furthermore, genetic alterations in SRCC differed from those in adenocarcinoma and mucinous adenocarcinoma. Conclusions: Our study revealed genomic changes in SRCC patients across different blood groups, which could advance the understanding and precise treatment of colorectal SRCC.