Prognostic significance of hemoglobin, albumin, lymphocyte, and platelet (HALP) score in breast cancer: a propensity score-matching study.

BACKGROUND: The hemoglobin-albumin-lymphocyte-platelet (HALP) score functions as a comprehensive index that assesses the systemic inflammatory response, nutritional, and immune status. This study aimed to explore the relationship between preoperative HALP score and the prognosis of BC patients and to develop predictive nomograms. METHODS: Clinicopathological data were collected for BC patients who underwent mastectomy between December 2010 and April 2014 from Sun Yat-sen University Cancer Center. The optimal cutoff value for HALP was determined by maximally selected rank statistics for overall survival data. Propensity score matching (PSM) was applied to develop comparable cohorts of high-HALP group and low-HALP group. Kaplan-Meier curves and Cox regression analyses were performed to determine the impact of HALP on BC patients. Prognostic nomograms were developed based on the multivariate Cox regression method. Then, the concordance index (C-index), calibration plots, and decision curves analysis (DCA) were applied to evaluate the prognostic performance of the nomograms. RESULTS: A total of 1,856 patients were included as the primary cohort, and 1,470 patients were matched and considered as the PSM cohort. In the primary cohort, the 5-year overall survival (OS) and progression-free survival (PFS) rates for high-HALP group (≥ 47.89) and low-HALP group (< 47.89) were 94.4% vs. 91.0% (P = 0.005) and 87.8% vs. 82.1% (P = 0.005), respectively. Similar results were observed in PSM cohort (5-year OS, 94.3% vs. 90.8%, P = 0.015; 5-year PFS, 87.5% vs. 83.2%, P = 0.036). Notably, multivariate Cox regression analysis in the PSM cohort showed that HALP could independently predict BC patient prognosis in both OS (HR: 0.596, 95%CI [0.405-0.875], P = 0.008) and PFS (HR: 0.707, 95%CI [0.538-0.930], P = 0.013). OS and PFS nomograms showed excellent predictive performance with the C-indexes of 0.783 and 0.720, respectively. The calibration plots and DCA also indicated the good predictability of the nomograms. Finally, subgroup analysis further demonstrated a favorable impact of HALP on both OS and PFS. CONCLUSION: Preoperative HALP score can be used as a reliable independent predictor of OS and PFS in BC patients, and the nomograms may provide a personalized treatment strategy.

Engineered low-pathogenic Helicobacter pylori as orally tumor immunomodulators for the stimulation of systemic immune response.

Gastric cancer constitutes a malignant neoplasm characterized by heightened invasiveness, posing significant global health threat. Inspired by the analysis that gastric cancer patients with Helicobacter pylori (H. pylori) infection have higher overall survival, whether H. pylori can be used as therapeutics agent and oral drug delivery system for gastric cancer. Hence, we constructed engineered H. pylori for gastric cancer treatment. A type Ⅱ H. pylori with low pathogenicity, were conjugated with photosensitizer to develop the engineered living bacteria NIR-triggered system (Hp-Ce6). Hp-Ce6 could maintain activity in stomach acid, quickly infiltrate through mucus layer and finally migrate to tumor region owing to the cell morphology and urease of H. pylori. H. pylori, accumulated in the tumor site, severed as vaccine to activate cGAS-STING pathway, and synergistically remodel the macrophages phenotype. Upon irradiation within stomach, Hp-Ce6 directly destroyed tumor cells via photodynamic effect inherited by Ce6, companied by inducing immunogenic tumor cell death. Additionally, Hp-Ce6 exhibited excellent biosafety with fecal elimination and minimal blood absorption. This work explores the feasibility and availability of H. pylori-based oral delivery platforms for gastric tumor and further provides enlightening strategy to utilize H. pylori invariably presented in the stomach as in-situ immunomodulator to enhance antitumor efficacy.

Significance of Pre-Treatment CALLY Score Combined with EBV-DNA Levels for Prognostication in Non-Metastatic Nasopharyngeal Cancer Patients: A Clinical Perspective.

Background: The C-reactive protein-albumin-lymphocyte (CALLY) score is a novel indicator associated with inflammation, immunity, and nutrition, utilized for cancer prognostic stratification. This study aimed to evaluate the integrated prognostic significance of the pre-treatment CALLY score and Epstein-Barr virus (EBV) DNA levels in nasopharyngeal carcinoma (NPC) patients and to develop prognostic models. Patients and Methods: A total of 1707 NPC patients from September 2015 to December 2017 were retrospectively enrolled. The cut-off point for the CALLY score, determined by maximum selected rank statistics, integrates with the published cut-off point for pre-EBV DNA to develop a comprehensive index. Subsequently, patients were randomly allocated in a 1:1 ratio into training and validation cohorts. Survival analysis was conducted using the Kaplan-Meier method with Log rank tests, and the Cox proportional hazards model was applied to identify independent prognostic factors for constructing predictive nomograms. The predictive ability of the nomograms were assessed through the concordance index (C-index), calibration curves, and decision curve analysis. Results: By integrating CALLY scores and EBV-DNA levels, patients were categorized into three risk clusters. Kaplan-Meier curves reveal significant differences in overall survival (OS), distant metastasis-free survival (DMFS), and locoregional relapse-free survival (LRRFS) outcomes among different risk groups (all P values < 0.05). Multivariate analysis revealed that CALLY-EBV DNA index serves as an independent prognostic factor for the OS, DMFS, and LRRFS. The prognostic nomograms based on the CALLY-EBV DNA index provided accurate predictions for 1-year, 3-year, and 5-year OS, DMFS, and LRRFS. Additionally, compared to the traditional TNM staging system, the nomograms exhibited enhanced discriminatory power, calibration capability, and clinical applicability. All results were in agreement with the validation cohort. Conclusion: The CALLY-EBV DNA index is an independent prognostic biomarker. The nomogram prediction models, constructed based on the CALLY-EBV DNA index, demonstrates superior predictive performance compared to the traditional TNM staging.

Does the Dose of Standard Adjuvant Chemotherapy Affect the Triple-negative Breast Cancer Benefit from Extended Capecitabine Metronomic Therapy? An Exploratory Analysis of the SYSUCC-001 Trial.

Purpose: Results from studies of extended capecitabine after the standard adjuvant chemotherapy in early stage triple-negative breast cancer (TNBC) were inconsistent, and only low-dose capecitabine from the SYSUCC-001 trial improved disease-free survival (DFS). Adjustment of the conventional adjuvant chemotherapy doses affect the prognosis and may affect the efficacy of subsequent treatments. This study investigated whether the survival benefit of the SYSUCC-001 trial was affected by dose adjustment of the standard adjuvant chemotherapy or not. Patients and Methods: We reviewed the adjuvant chemotherapy regimens before the extended capecitabine in the SYSUCC-001 trial. Patients were classified into "consistent" (standard acceptable dose) and "inconsistent" (doses lower than acceptable dose) dose based on the minimum acceptable dose range in the landmark clinical trials. Cox proportional hazards model was used to investigate the impact of dose on the survival outcomes. Results: All 434 patients in SYSUCC-001 trial were enrolled in this study. Most of patients administered the anthracycline-taxane regimen accounted for 88.94%. Among patients in the "inconsistent" dose, 60.8% and 47% received lower doses of anthracycline and taxane separately. In the observation group, the "inconsistent" dose of anthracycline and taxane did not affect DFS compared with the "consistent" dose. Moreover, in the capecitabine group, the "inconsistent" anthracycline dose did not affect DFS compared with the "consistent" dose. However, patients with "consistent" taxane doses benefited significantly from extended capecitabine (P=0.014). The sufficient dose of adjuvant taxane had a positive effect of extended capecitabine (hazard ratio [HR] 2.04; 95% confidence interval [CI] 1.02 to 4.06). Conclusion: This study found the dose reduction of adjuvant taxane might negatively impact the efficacy of capecitabine. Therefore, the reduction of anthracycline dose over paclitaxel should be given priority during conventional adjuvant chemotherapy, if patients need dose reduction and plan for extended capecitabine.

Predicting Survival of Patients with Nonmetastatic Breast Cancer Based on Fibrinogen-to-Albumin Ratio and Lymphocyte-to-Monocyte Ratio: A Nomogram-Based Assessment.

Background: Parameters of systemic inflammation have received attention as prognostic surrogates in various malignant tumors. Fibrinogen-to-albumin ratio (FAR) and lymphocyte-to-monocyte ratio (LMR) correlate with tumor growth and dissemination. We aimed to bring the combination of FAR and LMR (FAR-LMR) together to establish novel nomograms for survival and recurrence in nonmetastatic breast cancer patients. Methods: We retrospectively recruited 461 female patients with nonmetastatic breast cancer from January 2011 to December 2013 in our hospital and randomly assigned them into the training cohort (N = 318) and the validation cohort (N = 143). The potential predictive factors for overall survival (OS), locoregional recurrence-free survival (LRFS), and distant metastasis-free survival (DMFS) were assessed by Cox proportional hazards models and log-rank test. Results: Elevated FAR was associated with poor OS (p < 0.001) and DMFS (p = 0.02), whereas increased LMR was associated with satisfactory OS (p = 0.01) and LRFS (p = 0.01). High FAR combined with low LMR was associated with less favorable OS (p = 0.001), LRFS (p = 0.005), and DMFS (p = 0.003) Based on multivariate analysis, FAR-LMR, tumor size, lymph node metastasis, age, and pathologic status contributed to prognostic nomograms of OS, DMFS, and LRFS. Nomograms presented exceptional performance for 3-, 5-, and 8-year OS, DMFS, and LRFS prediction compared with clinical TNM stage. The C-index was significantly higher than that of TNM stage, either of FAR or LMR (3-year: 0.709 vs. 0.621 vs. 0.544 vs. 0.641, 5-year: 0.761 vs. 0.597 vs. 0.605 vs. 0.677, 8-year: 0.84 vs. 0.62 vs. 0.539 vs. 0.623). Conclusions: We developed and validated a convenient predictive model for the survival outcomes of patients with nonmetastatic breast cancer. The nomograms can be utilized as auxiliary tools to provide prognostic information.

Integrating Baseline Nutritional and Inflammatory Parameters with Post-Treatment EBV DNA Level to Predict Outcomes of Patients with De Novo Metastatic Nasopharyngeal Carcinoma Receiving Chemotherapy Combination PD-1 Inhibitor.

OBJECTIVES: To develop and validate a prognostic nomogram based on baseline nutritional and inflammatory parameters for risk stratification in patients with de novo metastatic nasopharyngeal carcinoma (dmNPC) receiving chemotherapy combination programmed death-1 (PD-1) inhibitor. METHODS: This retrospective study analyzed 131 patients with dmNPC (88 and 43 in the training and validation cohorts, respectively) between March 2017 and November 2020. All these patients received chemotherapy combined with PD-1 inhibitor treatment. We identified independent risk factors using univariate and multivariate Cox regression analyses and established a nomogram to predict the progression-free survival (PFS). The predictive accuracy of the nomogram was evaluated and independently validated. RESULTS: Baseline nutritional risk index (NRI), prognostic nutritional index (PNI), systemic immune-inflammation index (SII), uric acid (UA), and post-treatment Epstein-Barr virus (EBV) DNA were used to develop a nomogram that could divide patients into favorable- and unfavorable-prognosis groups. The median PFS (mPFS) was significantly longer in the favorable-prognosis group compared to the unfavorable-prognosis group (35.10 months [95% CI: 27.36-42.84] vs. 7.23 months [95% CI: 6.50-7.97]; p = 0.001). All results were confirmed in the validation cohort. CONCLUSIONS: The proposed model improved the prognostic risk stratification for patients with dmNPC undergoing chemotherapy combined with PD-1 inhibitor treatment.

Integrating pretreatment MRI-detected nodal features and Epstein-Barr virus DNA to identify optimal candidates for intensity-modulated radiotherapy alone in patients with stage II nasopharyngeal carcinoma.

OBJECTIVES: To develop and validate a prognostic nomogram based on MRI-detected features of retropharyngeal and cervical lymph nodes and Epstein-Barr virus (EBV) DNA in patients with stage II nasopharyngeal carcinoma (NPC) to distinguish low-risk patients for whom intensity-modulated radiotherapy (IMRT) alone is sufficient. METHODS: This retrospective study enrolled 894 patients with stage II NPC (596 and 298 in the training and validation cohorts, respectively) with pretreatment MRI between August 2010 and May 2019. All patients received IMRT with or without additional chemotherapy. We identified independent risk factors using univariate and multivariate Cox regression analyses. Survival was compared using Kaplan-Meier curves with the log-rank test. RESULTS: Independent factors derived from the multivariate analysis include cervical nodal necrosis (CNN), the extracapsular spread (ECS) of cervical and retropharyngeal lymph nodes, and gamma-glutamyl transferase (γ-GGT). Nomograms A, B, and C were established based on the clinical [tumor-node-metastasis (TNM) stage + Epstein-Barr virus (EBV) DNA], the clinical-radiological [all independent predictors] and the combined models [the clinical-radiological model + EBV DNA], respectively. Nomogram C (C-index 0.769 [0.718-0.820]) demonstrated better risk discrimination than nomogram B (0.762 [0.715-0.809]), nomogram A (0.619 [0.564-0.674]), and the TNM stage (0.560 [0.509-0.611]). In the low-risk group divided by nomogram C, no significant survival differences were observed between patients treated with radiotherapy (RT) alone and other regimens including additional chemotherapy. CONCLUSIONS: The nomogram combining MRI-detected retropharyngeal and cervical lymph node features with pretreatment EBV-DNA improved the prognostic risk stratification for stage II NPC.

Prognostic value and immune landscapes of TERT promoter methylation in triple negative breast cancer.

Background: Treatment options for patients with triple-negative breast cancer (TNBC) remain limited to mainstay therapies owing to a lack of efficacious therapeutic targets. Accordingly, there is an urgent need to discover and identify novel molecular targets for the treatment and diagnosis of this disease. In this study, we analyzed the correlation of telomerase reverse transcriptase (TERT) methylation status with TERT expression, prognosis, and immune infiltration in TNBC and identified the role of TERT methylation in the regulation TNBC prognosis and immunotherapy. Methods: Data relating to the transcriptome, clinicopathological characteristics and methylation of TNBC patients were obtained from The Cancer Genome Atlas (TCGA) database. TERT expression levels and differential methylation sites (DMSs) were detected. The correlations between TERT expression and DMSs were calculated. Kaplan-Meier curves was plotted to analyze the relationship between the survival of TNBC patients and the DMSs. The correlations of DMSs and TERT expression with several immunological characteristics of immune microenvironment (immune cell infiltration, immunomodulators, immune-related biological pathways, and immune checkpoints) were assessed. The results were validated using 40 TNBC patients from Sun Yat-sen University Cancer Center (SYSUCC). Results: Six DMSs were identified. Among them, four sites (cg11625005, cg07380026, cg17166338, and cg26006951) were within the TERT promoter, in which two sites (cg07380026 and cg26006951) were significantly related to the prognosis of patients with TNBC. Further validation using 40 TNBC samples from SYSUCC showed that the high methylation of the cg26006951 CpG site was associated with poor survival prognosis (P=0.0022). TERT expression was significantly correlated with pathological N stage and clinical stage, and cg07380026 were significantly associated with pathological T and N stages in the TCGA cohort. Moreover, the methylation site cg26006951, cg07380026 and TERT expression were significantly correlated with immune cell infiltration, common immunomodulators, and the level of the immune checkpoint receptor lymphocyte activation gene 3 (LAG-3) in TNBC patients. Conclusion: TERT promotertypermethylation plays an important role in TERT expression regulation and tumor microenvironment in TNBC. It is associated with overall survival and LAG-3 expression. TERT promoter hypermethylation may be a potential molecular biomarker for predicting response to the TERT inhibitors and immune checkpoint inhibitors in TNBC.

Intelligent Pd1.7Bi@CeO2 Nanosystem with Dual-Enzyme-Mimetic Activities for Cancer Hypoxia Relief and Synergistic Photothermal/Photodynamic/Chemodynamic Therapy.

Reactive oxygen species-mediated therapeutic strategies, including chemodynamic therapy (CDT) and photodynamic therapy (PDT), have exhibited translational promise for effective cancer management. However, monotherapy often ends up with the incomplete elimination of the entire tumor due to inherent limitations. Herein, we report a core-shell-structured Pd1.7Bi@CeO2-ICG (PBCI) nanoplatform constructed by a facile and effective strategy for synergistic CDT, PDT, and photothermal therapy. In the system, both Pd1.7Bi and CeO2 constituents exhibit peroxidase- and catalase-like characteristics, which not only generate cytotoxic hydroxyl radicals (•OH) for CDT but also produce O2 in situ and relieve tumor hypoxia for enhanced PDT. Furthermore, upon 808 nm laser irradiation, Pd1.7Bi@CeO2 and indocyanine green (ICG) coordinately prompt favorable photothermia, resulting in thermodynamically amplified catalytic activities. Meanwhile, PBCI is a contrast agent for near-infrared fluorescence imaging to determine the optimal laser therapeutic window in vivo. Consequently, effective tumor elimination was realized through the above-combined functions. The as-synthesized unitary PBCI theranostic nanoplatform represents a potential one-size-fits-all approach in multimodal synergistic therapy of hypoxic tumors.

Neutrophil extracellular traps (NETs)-related lncRNAs signature for predicting prognosis and the immune microenvironment in breast cancer.

Background: Neutrophil extracellular traps (NETs) are closely associated to tumorigenesis and development. However, the relationship between NETs-related long non-coding RNAs (lncRNAs) and the characteristics of breast tumor remains an enigma. This study aimed to explore the clinical prognostic value of NETs-related lncRNAs, their correlation with the tumor microenvironment (TME) and their predictive ability of drug sensitivity in patients with breast cancer (BC). Methods: The expression profiles of RNA-sequencing and relevant clinical data of BC patients were extracted from TCGA database. The co-expression network analysis, univariable, least absolute shrinkage and selection operator (LASSO) and multivariable Cox algorithms were employed to construct the NETs-related lncRNAs signature. A nomogram was established and validated to explore the clinical application. Furthermore, the immune microenvironment and drug sensitivity for BC with different prognostic risks were explored. Finally, the expression pattern of lncRNAs was validated using qRT-PCR in BC tissues and their adjacent non-cancerous tissues. Results: Based on NETs-related lncRNAs, a prognostic risk model consisted of 10 lncRNAs (SFTA1P, ACTA2-AS1, AC004816.2, AC000067.1, LINC01235, LINC01010, AL133467.1, AC092919.1, AL591468.1, and MIR200CHG) was established. The Kaplan-Meier analysis showed that the overall survival (OS) was significantly better in low-risk BC patients than in high-risk BC patients (P training cohort < 0.001, P validation cohort = 0.009). The nomogram also showed good predictive accuracy for OS of BC individuals in both training and validation cohorts. The function enrichment analysis revealed that high-risk group was mainly enriched in immune-related functions and pathways, and the tumor mutation burden in this group was markedly higher than that in the low-risk group (p = 0.022). Moreover, significant differences were observed in immune cells, immune functions and immune checkpoint genes among BC patients at different risks (p < 0.05). The response to chemotherapeutic agents and immunotherapy were also closely related with the expression of NETs-related lncRNAs (p < 0.001). The expression of lncRNAs from experimental validation were generally consistent with the bioinformatics analysis results. Conclusion: Our study provided a novel prognostic model for BC and yielded strong scientific rationale for individualized treatment strategies, elucidating immunotherapy in BC patients.

A Prognostic Model Based on Nutritional Risk Index in Operative Breast Cancer.

BACKGROUND: The nutritional risk index (NRI) is an independent prognostic factor for overall survival in various cancers, but its prognostic value in breast cancer remains unclear. This study aimed to explore the relationship between the NRI and overall survival (OS) in breast cancer and to develop a predictive nomogram. METHODS: We retrospectively enrolled 1347 breast cancer patients who underwent mastectomy or lumpectomy between January 2011 and November 2012. Using a cutoff value of 110.59, patients were divided into a high-NRI group and a low-NRI group. OS was compared between the two groups. Clinicopathological factors independently associated with survival were used to construct a predictive nomogram. RESULTS: Of the 1347 patients, 534 patients were classified as high NRI and 813 as low NRI. OS was significantly shorter in low-NRI patients. The 3- and 5-year OS rates were 87.3% and 73.4%, respectively, in the high-NRI group whereas they were 83.0% and 67.2%, respectively, in the low-NRI group. Cox regression analysis found that histopathological type, tumor size, lymph node status, progesterone receptor (PR) status, Ki-67, and NRI were independently associated with OS. CONCLUSIONS: NRI is an independent prognostic factor of OS in breast cancer patients. The proposed nomogram model may be a useful tool for individualized survival prediction.

SHMT2 promotes tumor growth through VEGF and MAPK signaling pathway in breast cancer.

Cancer cells modulate their metabolic activities to adapt to their growth and proliferation. Despite advances in breast cancer biology having led to the widespread use of molecular targeted therapy and hormonal drugs, the molecular mechanisms in metabolism related to the regulation of breast cancer cell proliferation are still poorly understood. Here, we investigate the possible role of SHMT2, a key enzyme in serine metabolism, in breast cancer. Firstly, SHMT2 is found highly expressed in both breast cancer cells and tissues, and patients with high expression of SHMT2 have a worse prognosis. Moreover, the intervention of SHMT2 by either knockdown or over-expression in vitro induces the effect on breast cancer proliferation. Mechanistically, RNA-seq shows that over-expression of SHMT2 affect multiple signaling pathways and biological process in breast cancer cells. Furthermore, we confirm that SHMT2 promotes breast cancer cell growth through MAPK and VEGF signaling pathways. Finally, we verify the role of SHMT2 in promoting breast cancer growth in the xenograft tumor model. Our results indicate that SHMT2 plays a critical role in regulating breast cancer growth through MAPK, and VEGF signaling pathways, and maybe serve as a therapeutic target for breast cancer therapy.

M1 stage subdivisions based on 18F-FDG PET-CT parameters to identify locoregional radiotherapy for metastatic nasopharyngeal carcinoma.

Purpose: To establish a risk classification of de novo metastatic nasopharyngeal carcinoma (mNPC) patients based on 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET-CT) radiomics parameters to identify suitable candidates for locoregional radiotherapy (LRRT). Methods: In all, 586 de novo mNPC patients who underwent 18F-FDG PET-CT prior to palliative chemotherapy (PCT) were involved. A Cox regression model was performed to identify prognostic factors for overall survival (OS). Candidate PET-CT parameters were incorporated into the PET-CT parameter score (PPS). Recursive partitioning analysis (RPA) was applied to construct a risk stratification system. Results: Multivariate Cox regression analyses revealed that total lesion glycolysis of locoregional lesions (LRL-TLG), the number of bone metastases (BMs), metabolic tumor volume of distant soft tissue metastases (DSTM-MTV), pretreatment Epstein-Barr virus DNA (EBV DNA), and liver involvement were independent prognosticators for OS. The number of BMs, LRL-TLG, and DSTM-MTV were incorporated as the PPS. Eligible patients were divided into three stages by the RPA-risk stratification model: M1a (low risk, PPSlow + no liver involvement), M1b (intermediate risk, PPSlow + liver involvement, PPShigh + low EBV DNA), and M1c (high risk, PPShigh + high EBV DNA). PCT followed by LRRT displayed favorable OS rates compared to PCT alone in M1a patients (p < 0.001). No significant survival difference was observed between PCT plus LRRT and PCT alone in M1b and M1c patients (p > 0.05). Conclusions: The PPS-based RPA stratification model could identify suitable candidates for LRRT. Patients with stage M1a disease could benefit from LRRT.

Pan-Immune-Inflammation Value: A New Prognostic Index in Operative Breast Cancer.

Background: To build a predictive scoring model based on simple immune and inflammatory parameters to predict postoperative survival in patients with breast cancer. Methods: We used a brand-new immuno-inflammatory index-pan-immune-inflammation value (PIV)-to retrospectively evaluate the relationship between PIV and overall survival (OS), and based on the results of Cox regression analysis, we established a simple scoring prediction model based on several independent prognostic parameters. The predictive accuracy of the model was evaluated and independently validated. Results: A total of 1,312 patients were included for analysis. PIV was calculated as follows: neutrophil count (109/L) × platelet count (109/L) × monocyte count (109/L)/lymphocyte count (109/L). According to the best cutoff value of PIV, we divided the patients into two different subgroups, high PIV (PIV > 310.2) and low PIV (PIV ≤ 310.2), associated with significantly different survival outcomes (3-year OS, 80.26% vs. 86.29%, respectively; 5-year OS, 62.5% vs. 71.55%, respectively). Six independent prognostic factors were identified and used to build the scoring system, which performed well with a concordance index (C-index) of 0.759 (95% CI: 0.715-0.802); the calibration plot showed good calibration. Conclusions: We have established and verified a simple scoring system for predicting prognosis, which can predict the survival of patients with operable breast cancer. This system can help clinicians implement targeted and individualized treatment strategies.

A Novel Inflammatory-Nutritional Prognostic Scoring System for Patients with Early-Stage Breast Cancer.

PURPOSE: We attempted to explore the prognostic value of baseline inflammatory and nutritional biomarkers at diagnosis in patients with early-stage breast cancer and develop a novel scoring system, the inflammatory-nutritional prognostic score (INPS). PATIENTS AND METHODS: We collected clinicopathological and baseline laboratory data of 1259 patients with early-stage breast cancer between December 2010 and November 2012 from Sun Yat-sen University Cancer Center. Eligible patients were randomly divided into training and validation cohorts (n = 883 and 376, respectively) in a 7:3 ratio. We selected the most valuable biomarkers to develop INPS by the least absolute shrinkage and selection operator (LASSO) Cox regression model. A prognostic nomogram incorporating INPS and other independent clinicopathological factors was developed based on the stepwise multivariate Cox regression method. Then, we used the concordance index (C-index), calibration plot, and time-dependent receiver operating characteristic (ROC) analysis to evaluate the prognostic performance and predictive accuracy of the predictive nomogram. RESULTS: Four inflammatory-nutritional biomarkers, including neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), prognostic nutritional index (PNI), and albumin-alkaline phosphatase ratio (AAPR), were selected using the LASSO Cox analysis to construct INPS, which remained an independent prognostic indicator per the multivariate Cox regression analysis. Patients were stratified into low- and high-INPS groups based on the cutoff INPS determined by the maximally selected rank statistics. The prognostic model for overall survival consisting of INPS and other independent clinicopathological indicators showed excellent discrimination with C-indexes of 0.825 (95% confidence interval [CI]: 0.786-0.864) and 0.740 (95% CI: 0.657-0.822) in the training and validation cohorts, respectively. The time-dependent ROC curves showed a higher predictive accuracy of our prognostic nomogram than that of traditional tumor-node-metastasis staging. CONCLUSION: Baseline INPS is an independent indicator of OS in patients with early-stage breast cancer. The INPS-based prognostic nomogram could be used as a practical tool for individualized prognostic predictions.

A survival prediction model and nomogram based on immune-related gene expression in chronic lymphocytic leukemia cells.

Introduction: There are many different chronic lymphoblastic leukemia (CLL) survival prediction models and scores. But none provide information on expression of immune-related genes in the CLL cells. Methods: We interrogated data from the Gene Expression Omnibus database (GEO, GSE22762; Number = 151; training) and International Cancer Genome Consortium database (ICGC, CLLE-ES; Number = 491; validation) to develop an immune risk score (IRS) using Least absolute shrinkage and selection operator (LASSO) Cox regression analyses based on expression of immune-related genes in CLL cells. The accuracy of the predicted nomogram we developed using the IRS, Binet stage, and del(17p) cytogenetic data was subsequently assessed using calibration curves. Results: A survival model based on expression of 5 immune-related genes was constructed. Areas under the curve (AUC) for 1-year survivals were 0.90 (95% confidence interval, 0.78, 0.99) and 0.75 (0.54, 0.87) in the training and validation datasets, respectively. 5-year survivals of low- and high-risk subjects were 89% (83, 95%) vs. 6% (0, 17%; p < 0.001) and 98% (95, 100%) vs. 92% (88, 96%; p < 0.001) in two datasets. The IRS was an independent survival predictor of both datasets. A calibration curve showed good performance of the nomogram. In vitro, the high expression of CDKN2A and SREBF2 in the bone marrow of patients with CLL was verified by immunohistochemistry analysis (IHC), which were associated with poor prognosis and may play an important role in the complex bone marrow immune environment. Conclusion: The IRS is an accurate independent survival predictor with a high C-statistic. A combined nomogram had good survival prediction accuracy in calibration curves. These data demonstrate the potential impact of immune related genes on survival in CLL.

A Model Combining Skeletal Muscle Mass and a Hematological Biomarker to Predict Survival in Patients With Nasopharyngeal Carcinoma Undergoing Concurrent Chemoradiotherapy.

BACKGROUND: Using the current tumor lymph node metastasis (TNM) staging system to make treatment decisions and predict survival in patients with nasopharyngeal carcinoma (NPC) lacks sufficient accuracy. Patients at the same stage often have different survival prognoses. METHODS: In the current study 802 NPC patients who underwent concurrent radiotherapy and chemotherapy from January 2010 to December 2014 at Sun Yat-sen University Cancer Center in China were retrospectively assessed. The optimal cut-off points for skeletal muscle index (SMI) and monocyte-to-lymphocyte ratio (MLR) were determined via receiver operating characteristic curves. SMI-MLR (S-M) grade and a nomogram were developed and used as clinical indicators in NPC patients. The consistency index (C-index) and a calibration curve were used to measure the accuracy and discriminative capacity of prediction. RESULTS: The predictive performance of S-M grade was better than that of TNM staging (C-index 0.639, range 0.578-0.701 vs. 0.605, range 0.545-0.665; p = 0.037). In multivariate analysis S-M grade, T stage, and N stage were independent prognostic factors. These three factors were then combined, yielding a nomogram with a C-index of 0.71 (range 0.64-0.77), indicating good predictive capacity. CONCLUSION: We developed and validated a prognostic parameter, S-M grade, which increased prediction accuracy significantly and can be combined with TNM staging to predict survival in patients with NPC undergoing concurrent chemoradiotherapy.