Prognostic Evaluation of Metastasis-Related Lymphocyte/Monocyte Ratio in Stage Ⅰ-Ⅲ Breast Cancer Receiving Chemotherapy

Lymphocyte-to-Monocyte Ratio Might Serve as a Prognostic Marker in Young Patients with Tongue Squamous Cell Carcinoma

BACKGROUND

Young patients with tongue squamous cell carcinoma (TSCC) mostly lack typical prognostic markers and face a dire prognosis. The aim of this study was to analyze the prognostic relevance of lymphocyte-to-monocyte ratio (LMR) in TSCC patients, with a special emphasis on patients under 45 years.

METHODS

This retrospective study included all patients primarily treated for TSCC. The prognostic relevance of LMR was investigated in terms of predicting the overallsurvival (OS) and disease-free survival (DFS).

RESULTS

A total of 74 patients were included and the young cohort (<45 years) comprised 27 individuals. The mortality and recurrence rates were 39.2% (n = 29) and 37.8% (n = 28), respectively. OS and DFS were significantly shorter in the low LMR group within the whole cohort. Furthermore, low LMR was associated with worse prognosis, particularly inferior OS (median OS 1.7 vs. 14.6 years, p = 0.0156) and worse DFS (median DFS 0.8 years vs. not reached, p = 0.0405) in the young patient cohort.

CONCLUSIONS

Our results reveal that pretreatment LMR might become a prognostic tool for young TSCC patients, especially due to its availability. However, further studies on larger cohorts are necessary to validate our results.

Prognostic evaluation of system immune-inflammatory index and prognostic nutritional index in double expressor diffuse large B-cell lymphoma

Predicting MYC and BCL2 double-expressor lymphoma prognosis using the system immune-inflammatory index (SII) and prognostic nutritional index (PNI) (DEL). From January 2015 to December 2021, 281 diffuse large B-cell lymphoma (DLBCL) wax blocks were used to make tissue chips. Screening double expressor lymphoma (DEL) instances involved immunocytochemistry and fluorescence in situ hybridization. Academic analysis used clinicopathological characteristics and follow-up data. SII, PNI, and DEL prognosis were correlated using univariate and multivariate cox regression analysis. The median age of 78 DEL patients is 60 (range: 43-74). SII and PNI cut-off values of 603.5, 3.07, and 144 predict PFS and OS well. Lower SII is associated with longer PFS (HR for SII = 0.34, 95% CI 0.15-0.76, P = 0.006; HR for NLR = 0.46, 95% CI 0.22-0.99, P = 0.048; HR for PLR = 0.39, 95% CI 0.17-0.94, P = 0.025; LMR = 0.39, 95%, CI 0.17-0.94, P = 0.025) and OS (HR for SII = 0.16, 95% CI 0.05-0.51, P = 0.005; HR for PNI = 0.20, 95% CI 0.06-0.62, P = 0.002). SII and PNI are promising predictors for twofold expressor DLBCL. Combining these increase prediction accuracy.

A Novel Albumin-Related Nutrition Biomarker Predicts Breast Cancer Prognosis in Neoadjuvant Chemotherapy: A Two-Center Cohort Study

BACKGROUND

Recently, there has been a growing focus on the prognostic significance of nutrition-related biomarkers. We attempted to explore the association between a novel albumin-related nutrition marker called "lymphocyte × albumin (LA)" and disease-free survival (DFS) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC).

METHODS

In total, 711 non-metastatic breast cancer patients who underwent NAC at two medical centers were retrospectively analyzed. We performed least absolute shrinkage and selection operator (LASSO) Cox regression analysis as well as multivariate Cox regression analyses to identify the variables associated with DFS and to establish a predictive nomogram.

RESULTS

The nomogram incorporated four variables based on the multivariate analysis of DFS in the training cohort: LA, ypN stage, ypT stage, and hormone receptor status. In comparison with the traditional TNM staging system, the nomogram demonstrated superior discrimination, calibration ability, and clinical usefulness in both the training set and internal and external validation sets. Furthermore, patients stratified into different risk groups resulted in significant differences in DFS.

CONCLUSIONS

LA is an independent prognostic biomarker, and LA-based prognostic nomogram offers a more precise assessment of DFS for breast cancer patients treated with NAC, potentially serving as a valuable tool for personalized prognostic predictions.

The benefit of treatment beyond progression with immune checkpoint inhibitors: a multi-center retrospective cohort study

OBJECTIVE

Treatment beyond progression (TBP) with immune checkpoint inhibitors (ICIs) is an evolving field due to the limitations of conventional imaging in response evaluation. However, real-life data on the benefit of TBP is scarce, especially from the limited resource settings and patients treated in the later lines. Therefore, we aimed to investigate the survival benefit of TBP with ICIs in patients with advanced tumors from a limited resource setting.

METHODS

For this multi-center retrospective cohort study, we included 282 patients treated with ICIs and had radiological progression according to RECIST 1.1 criteria. We evaluated post-progression survival according to the use of TBP (TBP and non-TBP groups) with univariate and multivariate analyses.

RESULTS

The cohort's median age was 61, and 84.4% were treated in the second or later lines. 82 (29.1%) of 282 patients continued on ICIs following the initial progression. In multivariate analyses, patients in the TBP group had improved post-progression survival compared to non-TBP (13.18 vs. 4.63 months, HR: 0.500, 95% CI: 0.349-0.717, p < 0.001). The benefit of the TBP was independent of the tumor type, treatment line, and age. Furthermore, TBP with ICIs remained associated with improved post-progression survival (HR: 0.600, 95% CI: 0.380-0.947, p = 0.028) after excluding the patients with no further treatment after progression in the non-TBP arm.

CONCLUSIONS

In this study, we observed that patients receiving ICIs beyond progression had considerably longer survival. Continuation of ICIs after progression should be considered a reasonable management option for patients with advanced cancer, specifically for patients with limited alternative options.

Establishment and validation of a novel prognostic model for non-virus-related hepatocellular carcinoma

Objective

The incidence of non-virus-related hepatocellular carcinoma (NV-HCC) in hepatocellular carcinoma (HCC) is steadily increasing. The aim of this study was to establish a prognostic model to evaluate the overall survival (OS) of NV-HCC patients.

Methods

Overall, 261 patients with NV-HCC were enrolled in this study. A prognostic model was developed by using LASSO-Cox regression analysis. The prognostic power was appraised by the concordance index (C-index), and the time-dependent receiver operating characteristic curve (TD-ROC). Kaplan–Meier (K–M) survival analysis was used to evaluate the predictive ability in the respective subgroups stratified by the prognostic model risk score. A nomogram for survival prediction was established by integrating the prognostic model, TNM stage, and treatment.

Results

According to the LASSO-Cox regression results, the number of nodules, lymphocyte-to-monocyte ratio (LMR), prognostic nutritional index (PNI), alkaline phosphatase (ALP), aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio (SLR) and C-reactive protein (CRP) were included for prognostic model construction. The C-index of the prognostic model was 0.759 (95% CI 0.723–0.797) in the development cohort and 0.796 (95% CI 0.737–0.855) in the validation cohort, and its predictive ability was better than TNM stage and treatment. The TD-ROC showed similar results. K–M survival analysis showed that NV-HCC patients with low risk scores had a better prognosis (P < 0.05). A nomogram based on the prognostic model, TNM stage, and treatment was constructed with sufficient discriminatory power with C-indexes of 0.78 and 0.85 in the development and validation cohort, respectively.

Conclusion

For NV-HCC, this prognostic model could predict an OS benefit for patients, which may assist clinicians in designing individualized therapeutic strategies.

Genomic mapping of copy number variations influencing immune response in breast cancer

Identification of genomic alterations that influence the immune response within the tumor microenvironment is mandatory in order to identify druggable vulnerabilities. In this article, by interrogating public genomic datasets we describe copy number variations (CNV) present in breast cancer (BC) tumors and corresponding subtypes, associated with different immune populations. We identified regulatory T-cells associated with the Basal-like subtype, and type 2 T-helper cells with HER2 positive and the luminal subtype. Using gene set enrichment analysis (GSEA) for the Type 2 T-helper cells, the most relevant processes included the ERBB2 signaling pathway and the Fibroblast Growth Factor Receptor (FGFR) signaling pathway, and for CD8+ T-cells, cellular response to growth hormone stimulus or the JAK-STAT signaling pathway. Amplification of ERBB2, GRB2, GRB7, and FGF receptor genes strongly correlated with the presence of type 2 T helper cells. Finally, only 8 genes were highly upregulated and present in the cellular membrane: MILR1, ACE, DCSTAMP, SLAMF8, CD160, IL2RA, ICAM2, and SLAMF6. In summary, we described immune populations associated with genomic alterations with different BC subtypes. We observed a clear presence of inhibitory cells, like Tregs or Th2 when specific chromosomic regions were amplified in basal-like or HER2 and luminal groups. Our data support further evaluation of specific therapeutic strategies in specific BC subtypes, like those targeting Tregs in the basal-like subtype.

Nomogram based on circulating lymphocyte subsets for predicting radiation pneumonia in esophageal squamous cell carcinoma

Purpose

Currently, the relationship between radiation pneumonia (RP) and circulating immune cell in patients with esophageal squamous cell carcinoma (ESCC) remains unclear. This study aimed to explore the relationship between RP and circulating lymphocyte subsets in patients with ESCC receiving chemoradiotherapy (CRT), and develop a nomogram model to predict RP. Since we should implement clinical intervention to ≥ grade 2 RP, a nomogram model for ≥ grade 2 RP was also established to provide an early warning.

Patients and methods

This study retrospectively included 121 patients with ESCC receiving CRT from Guangxi Medical University Cancer Hospital from 2013 to 2021. Independent factors associated with occurrence of RP and ≥ grade 2 RP were identified by univariate and multivariate logistic regression analysis in the training cohort, and incorporated into nomograms. The predictive accuracy and discrimination of the model was assessed using Concordance Index (C-index), calibration curve and decision curve analysis (DCA). And each model was internally validated. Additionally, to verify the optimized predictive performance of the nomograms, the area under the ROC curve (AUC) of each nomogram was compared to that of single independent risk factors, lung V10 and lung V20, respectively. Moreover, each model was further evaluated for risk stratification to identify populations at high risk of RP and ≥ grade 2 RP.

Results

Multivariate analysis suggested that TNM stage, post-RT percentage of CD8+ T cell, and lung V15 were independent predictive factors of RP. Besides, pre- and post-RT percentage of CD8+ T cell, and V15 were independent factors of ≥ grade 2 RP. The C-indexes of RP and ≥ grade 2 RP nomograms were 0.809 (95% CI: 0.715-0.903) and 0.787 (95% CI: 0.685-0.889) in the training cohort, respectively. And the C-indexes of RP and ≥ grade 2 RP nomograms were 0.718 (95% CI: 0.544-0.892) and 0.621 (95% CI: 0.404-0.837) in the validation cohort, respectively. The calibration curves showed that the predicted values of model agreed well with actual observations. Moreover, DCA results indicated the applicability and accuracy of the models to predict RP and ≥ grade 2 RP. After stratification, the incidence of the high-risk group was significantly higher than that of the low-risk group with respect to either RP or ≥ grade 2 RP.

Conclusion

TNM stage, post-RT percentage of CD8+ T cell, and lung V15 were the independent predictors of RP toxicity. Pre- and post-RT percentage of CD8+ T cell, and lung V15 were the independent factors of ≥ grade 2 RP toxicity. The nomograms based on circulating lymphocyte subsets can robustly predict RP and ≥ grade 2 RP, guiding clinicians in risk stratification and early intervention.