Discordant results have been generated regarding the prognostic role of Total Metabolic Tumor Volume (TMTV) in Follicular Lymphoma (FL). The use of prospective data and the adoption of the newly defined standardized SUV4 method for calculating TMTV may generate stronger evidence. We conducted a pre-planned post hoc analysis of the prospective multicenter randomized phase III FOLL12 trial for newly diagnosed high tumor burden FL (grade 1-3a), which mandated baseline staging with PET. Baseline PET/CT scans were reviewed centrally, and TMTV was calculated using the fixed threshold of SUV4. Kaplan-Meier and Cox regression were used for survival analysis. The primary study endpoint was Progression free Survival (PFS). A total of 689 FL patients were available for TMTV definition. Median TMTV was 161 mL (IQR 50 to 388 mL) and the best cutoff value was set at 180 mL. Patients with high TMTV had a significantly lower 5-year PFS compared to those with low TMTV: 59% (95% CI, 53-65%) vs. 74% (95% CI, 69-78%) HR 1.61 (95% CI, 1.24-2.09). Prognostic role of TMTV was independent of study arm, chemotherapy regimen, and FLIPI2. Combined with FLIPI-2, we identified three groups with different 5-yr PFS rates, with the lowest rates (51%) for patients with high TMTV and high FLIPI2. Combined TMTV and FLIPI model was also prognostic to predict the risk of early progression and of death. Applying the SUV4 standard method pre-treatment TMTV is confirmed as a strong and independent predictor of PFS in FL patients. Integrating TMTV with FLIPI-2 improves risk assessment.

Immune checkpoint blockade (ICB) therapy has transformed cancer treatment, yet many patients fail to respond. Employing single-cell multiomics, we unveil T cell dynamics influencing ICB response across 480 pan-cancer and 27 normal tissue samples. We identify four immunotherapy response-associated T cells (IRATs) linked to responsiveness or resistance and analyze their pseudotemporal patterns, regulatory mechanisms, and T cell receptor clonal expansion profiles specific to each response. Notably, transforming growth factor β1 (TGF-β1)+ CD4+ and Temra CD8+ T cells negatively correlate with therapy response, in stark contrast to the positive response associated with CXCL13+ CD4+ and CD8+ T cells. Validation with a cohort of 23 colorectal cancer (CRC) samples confirms the significant impact of TGF-β1+ CD4+ and CXCL13+ CD4+ and CD8+ T cells on ICB efficacy. Our study highlights the effectiveness of single-cell multiomics in pinpointing immune markers predictive of immunotherapy outcomes, providing an important resource for crafting targeted immunotherapies for successful ICB treatment across cancers.

Dedifferentiated liposarcoma (DDLPS) is one of the most common subtypes of soft tissue sarcoma with a highly variable clinical behavior. Despite advanced molecular approaches are exploring the genetic panorama of DDLPS progression, to date the driver genes of the aggressive clinical behavior in DDLPS have not been identified yet. Here, we used a Nanostring nCounter approach to study the gene expression profile of 60 selected genes involved in DDLPS progression, in a cohort of DDLPS with aggressive clinical behavior, in comparison to a cohort of DDLPS with indolent clinical behavior. We identified five genes whose expression is significantly and consistently altered in aggressive compared to indolent DDLPS. Moreover, by a clinical outcome analyses we found MAP3K12 gene expression linked with both a higher risk of metastases and death. We envisage that the identified genes could represent the first genes of a genetic signature able to predict the clinical evolution of a DDLPS.

Glioblastoma multiforme (GBM) is characterized by substantial heterogeneity and limited therapeutic options. As molecular approaches to central nervous system tumors have gained prominence, this study examined the roles of three genes, TWIST2, GATA3, and HES5, known to be involved in oncogenesis, developmental processes, and maintenance of cancer stem cell properties, which have not yet been extensively studied in GBM. This study is the first to present gene expression data for TWIST2, GATA3, and HES5 specifically within the context of GBM patient survival.

Gene expression data for TWIST2, GATA3, and HES5 were collected from GBM and normal brain tissues using datasets from The Cancer Genome Atlas via the Genomic Data Commons portal and the Genotype-Tissue Expression database. These data were rigorously analyzed using in silico methods.

All three genes were significantly more expressed in GBM tissues than in normal tissues. TWIST2 and GATA3 were linked to lower survival rates in GBM patients. Interestingly, higher HES5 levels were associated with better survival rates, suggesting a complex role that needs more investigation.

This study shows that TWIST2, GATA3, and HES5 could help predict outcomes in GBM patients. Our multigene model offers a better understanding of GBM and points to new treatment options, bringing hope for improved therapies and patient outcomes. This research advances our knowledge of GBM and highlights the potential of molecular diagnostics in oncology.

CT-based intratumoral and intertumoral heterogeneity indicators were integrated to develop a prognostic model for locally advanced gastric cancer (LAGC) patients undergoing neoadjuvant chemotherapy (NACT).

This retrospective study included 568 LAGC patients treated with NACT from two hospitals. The intratumor heterogeneity score (ITHscore) was developed to quantify the intratumoral heterogeneity of LAGCs on CT; intertumoral heterogeneity was characterized by combining the primary tumor (PT) and lymph node (LN) sizes on CT. CT indicators were measured on baseline and posttreatment CT scans; the reduction rates (%Δ) were calculated. The overall survival (OS) of all patients was recorded. Cox regression analysis was used to construct a preoperative survival prediction model (Pre-SPM) based on the baseline indicators and %Δ indicators. The predictive performance of Pre-SPM for OS was assessed. The clinicopathological data, including the ypTNM stage, were also collected to evaluate their impact on OS.

Patients with lower baseline ITHscore had better prognoses (p < 0.001). Approximately 13.01% of patients exhibited contradictory changes in PT and LN sizes. Cox regression analysis selected the baseline ITHscore, baseline PT area, %ΔPT, and %ΔLN to establish the Pre-SPM. In the external validation cohort, the c-index of Pre-SPM for predicting OS was 0.72, while the AUC for predicting 5-year OS was 0.73. After adjusting for the influence of clinicopathological features, including the ypTNM stage, Pre-SPM remained an independent prognostic factor.

The Pre-SPM model, combining intratumoral heterogeneity and intertumoral heterogeneity, has the potential to predict the OS of LAGC patients receiving NACT.

Question Increased tumor heterogeneity in LAGC affects prognosis, but effective non-invasive CT methods for assessing intratumoral and intertumoral heterogeneity are lacking. Findings ITHscore indicates intratumoral heterogeneity, while changes in PT and LN sizes reflect intertumoral heterogeneity. The Pre-SPM model, integrating both, independently predicts patient outcomes. Clinical relevance Pre-SPM enhances prognosis prediction by quantifying intratumoral and intertumoral heterogeneity, potentially guiding more personalized and effective treatment strategies for patients with LAGC.

Porto-sinusoidal vascular disorder (PSVD) is a rare vascular liver disorder characterised by specific histological findings in the absence of cirrhosis, which is poorly understood in terms of pathophysiology. While elevated hepatic copper content serves as diagnostic hallmark in Wilson disease (WD), hepatic copper content has not yet been investigated in PSVD.

Patients with a verified diagnosis of PSVD at the Medical University of Vienna and available hepatic copper content at the time of diagnosis of PSVD were retrospectively included. Elevated hepatic copper content was correlated with cholestatic changes and WD diagnostics in PSVD and analysed for liver-related outcomes (first/further hepatic decompensation/liver-related death).

Overall, 92 patients were included into this study (mean age 49 ± 16; 57% male; median hepatic copper content was 30 [IQR: 18-55] μg/g) of whom 29 (32%) had moderately (≥ 50 μg/g) and 4 (4%) strongly (≥ 250 μg/g) elevated hepatic copper content. Elevated levels of hepatic copper were associated with younger age in multivariable linear regression analysis. After adjusting for age, decompensation status and albumin, hepatic copper content was significantly associated with the outcome of interest (log, per 10; aHR: 1.60 [95% CI: 1.14-2.25]; p = 0.007). A hepatic copper cut-off at ≥ 90 μg/g identified PSVD patients with considerable risk of liver-related outcomes (at 2 years: 51% vs. 12%).

Elevated hepatic copper seems frequent in patients with PSVD even in the absence of cholestatic features, especially in young patients, which makes differential diagnosis to WD challenging. Since PSVD patients with elevated hepatic copper content had increased risk for liver-related outcomes, the pathomechanisms underlying hepatic copper accumulation in PSVD should be investigated as this may open new therapeutic avenues.

Primary mediastinal B-cell lymphoma (PMBL) is often cured with dose-dense anthracycline-based regimens but the prognosis at relapse or progression remains poor. While anti-CD19 CAR-T cell therapy has dramatically improved outcomes in relapsed or refractory large B-cell lymphoma, far less is known about their efficacy in PMBL. Using the systematic record of all patients treated with CAR-T cells prospectively included in the DESCAR-T registry in France, along with centrally reviewed positon-emission tomography (PET) imaging, we describe the outcomes and key determinants of treatment success in PMBL patients treated over a 6-year period. Among 82 patients infused in the registry we observed a best complete response (CR) rate, 2-year progression-free survival (PFS), and 2-year overall survival (OS) of 68.1%, 57.4%, and 73.8%, respectively. Outcomes were even better for the 62 patients infused with axicabtagene ciloleucel, with best CR rate, 2-year PFS, and 2-year OS reaching 74.5%, 70.4%, and 86.9%, respectively. Achieving a Deauville score of 1-4 or a ΔSUVmax reduction of more than 24% at the 1-month evaluation was associated with excellent outcomes, whereas increased total metabolic tumor volume baseline PET increased the risk of treatment failure. Surprisingly, neither the response to bridging therapy nor the type of bridging therapy (chemotherapy versus immune checkpoint inhibitors) were associated with long-term outcomes. In conclusion, this study confirms that anti-CD19 CAR-T cells as a valid standard-of-care for relapsed and refractory PMBL and highlights key determinants of treatment success.

The pan-immune-inflammation value reflects the systemic inflammatory response, and tumor-infiltrating lymphocytes indicate a local immune response in rectal cancer. However, the association between systemic inflammatory response, as indicated by the pan-immune-inflammation value, and local immune responses in rectal cancer remains unclear. This study analyzed 915 treatment-naïve rectal cancer patients from the Peking Union Medical College Hospital and PLA General Hospital (PLAGH) cohorts who underwent radical surgery to investigate the relationship between the pan-immune-inflammation value and immune responses. Lower pan-immune-inflammation value was significantly associated with improved disease-free survival and cancer-specific survival. Multivariate Cox regression models identified the pan-immune-inflammation value as an independent prognostic factor. In the PLAGH cohort, patients with low pan-immune-inflammation values had higher immune cell levels, activated immune pathways, and increased expression of immune checkpoint genes according to RNA sequencing. Hematoxylin and eosin staining and immunohistochemical analysis revealed that lower pan-immune-inflammation value was associated with higher tumor-infiltrating lymphocyte density, more mature tertiary lymphoid structures, increased CD8+ T cells, and elevated human lymphocyte antigen class I expression. Conversely, patients with high pan-immune-inflammation values exhibited pathways linked to tumor progression, such as angiogenesis, epithelial-mesenchymal transition, hypoxia, KRAS signaling, and TGF-ß signaling. Among patients receiving anti-PD-1 therapy, responders had low pre- and post-treatment pan-immune-inflammation values. The pan-immune-inflammation value is a reliable marker associated with distinct immune microenvironment characteristics and can effectively predict disease-free survival, cancer-specific survival, and response to immunotherapy.

Allogeneic hematopoietic cell transplantation (allo-HCT) presents a potentially curative treatment for hematologic malignancies yet carries associated risks and complications. Continuous research focuses on predicting outcomes and identifying risk factors. Notably, the influence of CD34+ cell dose on overall survival (OS) has been the subject of numerous studies yielding contradictory results. We developed machine learning (ML) models to predict allo-HCT outcomes and, through the application of SHapley Additive exPlanations (SHAP), an explainable artificial intelligence (XAI) technique enabled the identification of new and clinically relevant feature-outcome relationships. In particular, we identified a clear interaction between CD34+ cell dose of peripheral blood stem cell (PBSC) grafts and patient age at allo-HCT for patients with acute leukemia. Results of multivariable analysis validated the interaction effect: in young patients with acute leukemia (aged ≤45 years), low dose of CD34+ cells (<4.3 × 106 CD34+/kg) was associated with better OS against high dose (≥7 ×106 CD34+/kg) (hazard ratio [HR], 0.38; p = 0.019), while for older patients with acute leukemia (>45 years), low CD34+ cell dose (<3.8 ×106 CD34+/kg) was associated with worse OS against high dose (≥6.1 ×106 CD34+/kg) (HR, 1.58; p = 0.033). In conclusion, our findings suggest that tailoring CD34+ cell dose by patient age may benefit patients with acute leukemia undergoing allo-HCT, while XAI showcases excellent proficiency in revealing such interactions.

This study aimed to investigate and propose novel approaches to calculate muscle quality index (MQI) using muscle mass derived from single-frequency bioelectrical impedance analysis (SF-BIA) and calf circumference in both unadjusted and body mass index (BMI)-adjusted forms. In addition, we examined their prognostic significance in patients with cancer.

A secondary analysis was conducted on a prospective cohort study of patients with cancer. Handgrip strength was measured. SF-BIA was conducted to estimate appendicular lean soft tissue (ALST, in kilograms). MQI was calculated using three approaches: (1) the ratio of handgrip strength to ALST (MQISF-BIA), (2) the ratio of handgrip strength to calf circumference (MQIcalf circumference), and (3) the ratio of handgrip strength to BMI-adjusted calf circumference (MQIadj. calf circumference). Maximally selected log-rank was calculated to estimate their cutoff values to predict survival.

Two hundred eighty-four patients were included (51.1% men; median age, 61 years). Solid tumors were the most frequent (89.8%). All approaches to MQI (MQISF-BIA, MQIcalf circumference, and MQIadj. calf circumference) were independent predictors of 6-month mortality. The found cutoffs were (1) MQISF-BIA (<1.52 for men, <0.63 for women), (2) MQIcalf circumference (<0.74 for men, <0.24 for women), and (3) MQIadj. calf circumference (<0.75 for men, <0.25 for women).

This study introduces MQISF-BIA, MQIcalf circumference, and MQIadj. calf circumference as future potential surrogate methods for computing MQI in clinical practice when other robust procedures are unavailable, pending further validation.

Background: Although immune checkpoint inhibitors (ICIs) have significantly improved cancer treatment, a substantial proportion of patients do not benefit from these therapies, revealing the crucial need to identify reliable biomarkers. Inflammatory markers, such as the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), pan-immune inflammation value (PIV), systemic inflammation response index (SIRI), lactate dehydrogenase (LDH), and C-reactive protein (CRP), may provide insights into treatment outcomes. Objectives: This study aimed to evaluate the prognostic value of multiple inflammatory markers in patients with cancer receiving ICI-based therapies. Methods: A retrospective analysis was performed on 226 patients treated with ICI-based therapies at a single center between 2012 and 2023. The inflammatory markers NLR, PIV, SII, SIRI, LDH, CRP, and albumin were assessed. Cut-off values were determined using maximally selected rank statistics, and overall survival (OS) and progression-free survival (PFS) were evaluated using the Kaplan-Meier method and Cox regression analysis. Results: High NLR, PIV, SII, SIRI, LDH, and CRP, as well as low albumin levels, were associated with worse OS and PFS (p < 0.001). In the multivariate analysis, high CRP, LDH, NLR, PIV, and SII independently predicted worse OS. Conclusions: Our findings confirm the prognostic utility of several inflammatory biomarkers in patients with cancer receiving ICIs, highlighting their potential for treatment stratification. Further studies are necessary to standardize cut-off values and validate these findings across broader, more diverse populations.

In a randomized clinical controlled trial (PA.3) conducted by the Canadian Cancer Trials Group, the effects of gemcitabine combined with the targeted drug erlotinib (GEM-E) versus gemcitabine alone (GEM) on patients with unresectable, locally advanced, or metastatic pancreatic cancer were studied. This trial statistically demonstrated that the GEM-E combination therapy moderately improves overall survival (OS) of patients. However, real-world analysis suggested that GEM-E for pancreatic cancer was not more effective than GEM. The heterogeneity in outcomes or treatment effect exist. Thus, we tried to find predictive biomarkers to identifying the heterogeneous patients.

Of the 569 eligible patients, 480 patients had plasma samples. Univariate and multivariate Cox proportional hazards model were used to identify baseline characteristics related to OS, and a risk adjusted Exponentially Weighted Moving Average (EWMA) control chart based on a weighted score test from the Cox model was constructed to monitor patients' survival risk. Maximally selected rank statistics were constructed to identifying the predictive biomarkers, in addition, a risk adjusted control chart based on a weighted score test from the Cox model was constructed to validating the predictive biomarkers, discover the patients who sensitive to the GEM-E or GEM.

Three baseline characteristics (ECOG performance status, extent of disease, and pain intensity) were identified related to prognosis. A risk-adjusted EWMA control chart was constructed and showed that GEM-E did improve OS in a few patients. Three biomarkers (BMP2, CXCL6, and HER2) were identified as predictive biomarkers based on maximum selected rank test, and using the risk-adjusted EWMA control chart to validate the reality and discover some patients who are sensitive to the GEM-E therapy.

In reality, GEM-E has not shown a significant advantage over GEM in the treatment of pancreatic cancer. However, we discovered some patients who are sensitive to the GEM-E therapy based on the predictive biomarkers, which suggest that the predictive biomarkers provide ideas for personalized medicine in pancreatic cancer.

With the advancement of high-throughput studies, an increasing wealth of high-dimensional multi-omics data is being collected from the same patient cohort. However, leveraging this multi-omics data to predict survival outcomes poses a significant challenge due to its complex structure.

In this article, we present a novel approach, the Adaptive Sparse Multi-Block Partial Least Squares (asmbPLS) Regression model, which introduces a dynamic assignment of penalty factors to distinct blocks within various PLS components, facilitating effective feature selection and prediction.

We compared the proposed method with several state-of-the-art algorithms encompassing prediction performance, feature selection and computation efficiency. We conducted comprehensive evaluations using both simulated data with various scenarios and a real dataset from the melanoma patients to validate the effectiveness and efficiency of the asmbPLS method. Additionally, we applied the lung squamous cell carcinoma (LUSC) dataset from The Cancer Genome Atlas (TCGA) to further assess the feature selection capability of asmbPLS.

The inherent nature of asmbPLS imparts it with higher sensitivity in feature selection compared to other methods. Furthermore, an R package called asmbPLS implementing this method is made publicly available.

Pulmonary hypertension (PH) is a serious disease, however simple tools to predict outcomes are lacking. In our previous investigation, we found that heart rate variability (HRV) and heart rhythm complexity (HRC) were associated with the detection and severity of PH, however their association with PH mortality remains unclear. The aim of this study was to investigate these metrics as a tool for determining long-term outcomes in PH patients. We enrolled 74 Asian PH patients with WHO PH group 1 or 4 at a single hospital in Taiwan between March 2012 and June 2018. After a median follow-up duration of 58 months (to January 2023), 22 patients had died. The patients who died had a significantly lower lean body mass index (BMI), impaired renal function, higher N-terminal pro B-type natriuretic peptide (NT-proBNP) level, lower very low-frequency (VLF), lower short-term detrended fluctuation analysis α1 (DFAα1), and lower multiscale entropy scale 5 value. In multivariable analysis, BMI, VLF and multiscale entropy scale 5 were significantly associated with survival. The best cut-off VLF and scale 5 values were 115.13 and 0.738, respectively. We then categorized the study population into three groups: both elevated VLF/scale 5 (group 1), either depressed VLF or depressed scale 5 (group 2), and both depressed VLF/scale 5 (group 3). The results showed that group 1 had the best outcomes, whereas group 3 had the worst survival (P < 0.001). Combining HRV and HRC metrics appears to be a good non-invasive tool to predict the long-term outcomes of patients with PH.

The relationship between long-term outcomes and operator experience for left atrial appendage occlusion (LAAO) is still unknown.

This study sought to explore the association between operator LAAO experience and one-year clinical outcomes.

The RECORD study (Registry to Evaluate Chinese Real-World Clinical Outcomes in Patients With AF Using the WATCHMAN Left Atrial Appendage Closure Technology; NCT03917563) was a multicenter, prospective registry that included patients with the WATCHMAN LAAO device (Boston Scientific) in China from April 1, 2019, to October 31, 2020. The current analyses included patients with solely LAAO from the registry; those who had concomitant LAAO and ablation/other procedures were excluded. The primary outcome was a composite endpoint of death, stroke, systemic embolism, and Bleeding Academic Research Consortium (BARC)-defined type 3 or 5 bleeding at 1 year.

A total of 1,547 LAAO patients and 111 operators were included. The mean CHA2DS2-VASc and HAS-BLED scores of patients were 4.0 ± 1.8 and 2.5 ± 1.1, respectively. The mean age of operators was 47.0 ± 7.2 years, 15 (13.5%) were female, and 52 (46.8%) were electrophysiologists. Utilizing maximally selected log-rank statistics, the thresholds to categorize an experienced operator were performing ≥32 LAAOs annually or ≥134 LAAOs in total. Performing ≥32 LAAOs annually is the better criterion than ≥134 LAAOs in total (absolute net reclassification index: 25.79%; P < 0.001). Compared with the ≥32 LAAO annually group, the <32 group was associated with a 1.8-fold (HRadjusted: 1.79; 95% CI: 1.16-2.78; P = 0.009) increase in the risk of the primary endpoint, and such risk in the <32 group can be reduced by ∼12% after performing each additional 5 cases (HRadjusted per 5 cases: 0.88; 95% CI: 0.78-0.99; P = 0.033).

Performing ≥32 LAAOs annually could be a threshold to categorize an experienced operator. Before reaching this threshold, the risk of death, stroke, systemic embolism, and BARC-defined type 3 or 5 bleeding decreased by 12% after every 5 cases performed.

Peroxisome proliferator-activated receptors (PPARs), including PPAR-α, PPAR-β/δ, and PPAR-γ, are involved in various cellular responses, including metabolism and cell proliferation. Increasing evidence suggests that PPARs are closely associated with tumorigenesis and metastasis. However, the exact role of PPARs in energy metabolism and cancer stem cell (CSC) proliferation remains unclear. This study investigated the role of PPARs in energy metabolism and tumorigenesis in ovarian CSCs. The expression of PPARs and fatty acid consumption as an energy source increased in spheroids derived from A2780 ovarian cancer cells (A2780-SP) compared with their parental cells. GW6471, a PPARα inhibitor, induced apoptosis in A2780-SP. PPARα silencing mediated by small hairpin RNA reduced A2780-SP cell proliferation. Treatment with GW6471 significantly inhibited the respiratory oxygen consumption of A2780-SP cells, with reduced dependency on fatty acids, glucose, and glutamine. In a xenograft tumor transplantation mouse model, intraperitoneal injection of GW6471 inhibited in vivo tumor growth of A2780-SP cells. These results suggest that PPARα plays a vital role in regulating the proliferation and energy metabolism of CSCs by altering mitochondrial activity and that it offers a promising therapeutic target to eradicate CSCs.

Chimeric antigen receptor (CAR) T-cell therapy fails to achieve durable responses in over 60% of relapsed/refractory (R/R) large B-cell lymphoma (LBCL) patients in the third or later line setting. After CAR-T failure, survival outcomes are heterogeneous and a prognostic model in this patient population is lacking. A training cohort of 216 patients with progressive disease (PD) after CAR-T from 12 Spanish centers was used to develop the Post-CAR Prognostic Index (PC-PI); primary endpoint was overall survival (OS) from CAR-T progression. Validation was performed in an external cohort from three different European centers (n = 204). The prognostic score incorporated five variables, assessed at time of PD to CAR-T: ECOG (> 0), hemoglobin (< 10 g/dL), LDH (≥ 2xULN), number of extranodal sites (> 1) and time from CAR-T to PD (< 4 months). Patients were classified in four risk groups with distinct OS (p-value < 0.05 in all comparisons). In the validation cohort, median OS in the low (31%), intermediate-low (26%), intermediate-high (17%) and high risk (26%) were 15.7, 7.1, 1.8 and 1.0 months, respectively (p < 0.05 in all comparisons). Results were consistent following adjustment for subsequent treatment. In the external cohort, the PC-PI showed a C-statistic of 0.79 (95%CI 0.76-0.82), outperforming IPI and R-IPI. In conclusion, the PC-PI score is a novel tool for OS prediction and could facilitate risk-adapted management of LBCL patients relapsing after CAR T-cells. Additionally, these results will help stratification and interpretation of trials and real-world data incorporating CART-exposed patients.

To evaluate the prognostic value of peripheral lymphocyte count (PLC) in the breast cancer patients after breast-conserving surgery (BCS) with radiotherapy (RT).

This post hoc analysis was performed using data of 628 patients from a phase III, randomized controlled trial comparing hypofractionated RT (HFRT) with conventional fractionated RT (CFRT) after BCS. PLCs were obtained before, during, and after RT until the 1-year follow-up. The optimal cut-off PLCs were determined using the maxstat package in R. Survival rates were estimated using the Kaplan-Meier method and compared with the log-rank test.

A total of 275 (46.1 %) patients developed lymphopenia during RT, among them, 17 (2.8 %) had grade 3 lymphopenia and no one developed grade 4 lymphopenia. With a median follow-up of 110.8 months, patients with pre-RT PLCs of < 1.77 × 109/L had a significantly lower 10-year breast cancer-specific survival (BCSS) rate (P = 0.013) and overall survival (OS) rate (P = 0.026). Patients with a nadir PLC of < 1.35 × 109/L had a significantly poorer 10-year OS rate (P = 0.048). Multivariate analysis showed that a pre-RT PLC of < 1.77 × 109/L was an independent factor influencing BCSS and OS, while the effect of the nadir PLC did not remain significant. Neither PLC nor lymphopenia recovery at post-RT 1, 3, and 6 months and 1 year was associated with survival.

Radiation-induced lymphopenia in patients with breast cancer after BCS tends to be mild. The lower pre-RT PLC predicted poorer survival.

Zinc and selenium are essential trace elements involved in important (patho)physiological processes. The prevalence and prognostic implications of zinc and selenium deficiency in patients with advanced chronic liver disease (ACLD) remain unknown.

We determined serum zinc and selenium concentrations in 309 patients with ACLD undergoing hepatic venous pressure gradient (HVPG) measurement between 2019 and 2022. We evaluated the prevalence of zinc/selenium deficiency and assessed its association with severity of ACLD and liver-related events (LRE, i.e. first/further hepatic decompensation/liver-related death).

Among 309 ACLD patients (median: age: 57 [IQR: 50-64], MELD: 11 [IQR: 9-16], HVPG: 17 [IQR: 11-20]), 73% (227) and 63% (195) were deficient in zinc and selenium, respectively. Decompensated (dACLD) patients showed significantly lower serum zinc (median: 48 [IQR: 38-59] vs. compensated, cACLD: 65 [IQR: 54-78], p < 0.001) and selenium levels (median: 4.9 [IQR 4.0-6.2] vs. cACLD: 6.1 [IQR 5.1-7.3], p < 0.001). Significant correlations of zinc/selenium levels were found with MELD (zinc: ρ = -0.498, p < 0.001; selenium: ρ = -0.295, p < 0.001), HVPG (zinc: ρ = -0.400, p < 0.001; selenium: ρ = -0.157, p = 0.006) and liver disease-driving mechanisms (IL6, bile-acid homeostasis). On multivariable analysis, low zinc/selenium levels, age and MELD remained independently associated with LRE.

Zinc and selenium deficiencies are common in ACLD patients especially with higher MELD and HVPG. Low zinc and selenium levels independently predicted hepatic decompensation and liver-related death. The effect of zinc/selenium supplementation in ACLD should be investigated in future trials.

Immune checkpoint blockade (ICB) therapy has brought significant advancements to the field of oncology. However, the diverse responses among patients highlight the need for more accurate predictive tools. In this study, insights are drawn from tumor-immunology pathways, and a novel network-based ICB immunotherapeutic signature, termed ICBnetIS, is constructed. The signature is derived from advanced biological network-based computational strategies involving co-expression networks and molecular interactions networks. The efficacy of ICBnetIS is established through its association with enhanced patient survival and a robust immune response characterized by diverse immune cell infiltration and active anti-tumor immune pathways. The validation process positions ICBnetIS as an effective tool in predicting responses to ICB therapy, analyzing ICB data from a broad collection of over 700 samples from multiple cancer types of more than 15 datasets. It achieves an aggregated prediction AUC of 0.784, which outperforms the other nine renowned immunotherapeutic signatures, indicating the superior predictive capability of ICBnetIS. To sum up, the findings suggest ICBnetIS as a potent tool in predicting ICB therapy responses, offering significant implications for patient selection and treatment optimization in oncology. The study highlights the role of ICBnetIS in advancing personalized treatment strategies, potentially transforming the clinical landscape of ICB therapy.

A growing body of research indicates significant differences between left-sided colon cancers (LCC) and right-sided colon cancers (RCC). Pan-immune-inflammation value (PIV) is a systemic immune response marker that can predict the prognosis of patients with colon cancer. However, the specific distinction between PIV of LCC and RCC remains unclear.

To investigate the prognostic and clinical significance of PIV in LCC and RCC patients.

This multicenter retrospective cohort study included 1510 patients with colon cancer, comprising 801 with LCC and 709 with RCC. We used generalized lifting regression analysis to evaluate the relative impact of PIV on disease-free survival (DFS) in these patients. Kaplan-Meier analysis, as well as univariate and multivariate analyses, were used to examine the risk factors for DFS. The correlation between PIV and the clinical characteristics was statistically analyzed in these patients.

A total of 1510 patients {872 female patients (58%); median age 63 years [interquartile ranges (IQR): 54-71]; patients with LCC 801 (53%); median follow-up 44.17 months (IQR 29.67-62.32)} were identified. PIV was significantly higher in patients with RCC [median (IQR): 214.34 (121.78-386.72) vs 175.87 (111.92-286.84), P < 0.001]. After propensity score matching, no difference in PIV was observed between patients with LCC and RCC [median (IQR): 182.42 (111.88-297.65) vs 189.45 (109.44-316.02); P = 0.987]. PIV thresholds for DFS were 227.84 in LCC and 145.99 in RCC. High PIV (> 227.84) was associated with worse DFS in LCC [PIV-high: Adjusted hazard ratio (aHR) = 2.39; 95% confidence interval: 1.70-3.38; P < 0.001] but not in RCC (PIV-high: aHR = 0.72; 95% confidence interval: 0.48-1.08; P = 0.114).

These findings suggest that PIV may predict recurrence in patients with LCC but not RCC, underscoring the importance of tumor location when using PIV as a colon cancer biomarker.

Background Bone marrow lesions (BMLs) are a known risk factor for incident knee osteoarthritis (OA), and deep learning (DL) methods can assist in automated segmentation and risk prediction. Purpose To develop and validate a DL model for quantifying tibiofemoral BML volume on MRI scans in knees without radiographic OA and to assess the association between longitudinal BML changes and incident knee OA. Materials and Methods This retrospective study included knee MRI scans from the Osteoarthritis Initiative prospective cohort (February 2004-October 2015). The DL model, developed between August and October 2023, segmented the tibiofemoral joint into 10 subregions and measured BML volume in each subregion. Baseline and 4-year follow-up MRI scans were analyzed. Knees without OA at baseline were categorized into three groups based on 4-year BML volume changes: BML-free, BML regression, and BML progression. The risk of developing radiographic and symptomatic OA over 9 years was compared among these groups. Results Included were 3869 non-OA knees in 2430 participants (mean age, 59.5 years ± 9.0 [SD]; female-to-male ratio, 1.3:1). At 4-year follow-up, 2216 knees remained BML-free, 1106 showed an increase in BML volume, and 547 showed a decrease in BML volume. BML progression was associated with a higher risk of developing radiographic knee OA compared with remaining BML-free (hazard ratio [HR] = 3.0; P < .001) or BML regression (HR = 2.0; P < .001). Knees with BML progression also had a higher risk of developing symptomatic OA compared with BML-free knees (HR = 1.3; P < .001). Larger volume changes in BML progression were associated with a higher risk of developing both radiographic OA (HR = 2.0; P < .001) and symptomatic OA (HR = 1.7; P < .001). In almost all subchondral plates, especially the medial femur and tibia, BML progression was associated with a higher risk of developing both radiographic and symptomatic OA compared with remaining BML-free. Conclusion Knees with BML progression, according to subregion and extent of volume changes, were associated with an increased risk of OA compared with BML-free knees and knees with BML regression, highlighting the potential utility of monitoring BML volume changes in evaluating interventions to prevent OA development. ClinicalTrials.gov Identifier: NCT00080171 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Said and Sakly in this issue.

To determine the additional value of peritumoral radiomics in predicting overall survival (OS) in surgically resected non-small cell lung cancer (NSCLC) and its correlation with pathological findings.

A total of 526 patients with surgically resected NSCLC were included (191 training, 160 internal validation, and 175 external validation cohorts). CT images were used to segment the gross tumor volume (GTV) and peritumoral volume (PTV) within distances of 3, 6, 9 mm from the tumor boundary (PTV3, PTV6, and PTV9), and radiomic features were extracted. Four prognostic models for OS (GTV, GTV + PTV3, GTV + PTV6, and GTV + PTV9) were constructed using the training cohort. The prognostic ability and feature importance were evaluated using the validation cohorts. Pathological findings were compared between the two patient groups (n = 30 for each) having the top 30 and bottom 30 values of the most important peritumoral feature.

The GTV+ PTV3 models exhibited the highest predictive ability, which was higher than that of the GTV model in the internal validation cohort (C-index: 0.666 vs. 0.616, P = 0.027) and external validation cohort (C-index: 0.705 vs. 0.656, P = 0.048). The most important feature was GLDM_Dependence_Entropy, extracted from PTV3. High peritumoral GLDM_Dependence_Entropy was associated with a high proportion of invasive histological types, tumor spread through air spaces, and tumor-infiltrating lymphocytes (all P < 0.05).

The GTV and PTV3 combination demonstrated a higher prognostic ability, compared to GTV alone. Peritumoral radiomic features may be associated with various pathological prognostic factors.

Patients with liver cirrhosis often face a grave threat from infected ascites (IA). However, a well-established prognostic model for this complication has not been established in routine clinical practice. Therefore, we aimed to assess mortality risk in patients with liver cirrhosis and IA.

We conducted a retrospective study across three tertiary hospitals, enrolling 534 adult patients with cirrhotic liver and IA, comprising 465 with spontaneous bacterial peritonitis (SBP), 34 with bacterascites (BA), and 35 with secondary peritonitis (SP). To determine the attributable mortality risk linked to IA, these patients were matched with 122 patients with hydropic decompensated liver cirrhosis but without IA. Clinical, laboratory, and microbiological parameters were assessed for their relation to mortality using univariable analyses and a multivariable random forest model (RFM). Least absolute shrinkage and selection operator (Lasso) regression model was used to establish an easy-to-use mortality prediction score.

The in-hospital mortality risk was highest for SP (39.0%), followed by SBP (26.0%) and BA (25.0%). Besides illness severity markers, microbiological parameters, such as Candida spp., were identified as the most significant indicators for mortality. The Lasso model determined 15 parameters with corresponding scores, yielding good discriminatory power (area under the receiver operating characteristics curve = 0.89). Counting from 0 to 83, scores of 20, 40, 60, and 80 corresponded to in-hospital mortalities of 3.3%, 30.8%, 85.2%, and 98.7%, respectively.

We developed a promising mortality prediction score for IA, highlighting the importance of microbiological parameters in conjunction with illness severity for assessing patient outcomes.

Recurrence risks of cancer patient can change during treatment as a result of treatment-related tumor evolution. However, biomarkers that can monitor these changes are lacking. Here, we investigated whether tracking circulating tumor DNA (ctDNA) dynamics through liquid biopsy can inform real-time recurrence risk. Nasopharyngeal carcinoma (NPC) provides an ideal model where cell-free Epstein-Barr virus (EBV) DNA (cfEBV DNA), a ctDNA, can be sensitively detected. We conducted the EP-SEASON study (NCT03855020) and prospectively recruited 1,000 NPC patients undergoing per-protocol cfEBV DNA assessments at 11 time points and receiving sequential chemo-radiotherapy. Longitudinal cfEBV DNA displayed distinct patterns during neoadjuvant chemotherapy and radiotherapy. Despite the prognostic significance of cfEBV DNA at each time point, real-time recurrence risks changed in sync with cfEBV DNA dynamics. Furthermore, we identified phenotypes of whole-course ctDNA changing dynamics associated with different survival outcomes. In conclusion, tracking longitudinal on-treatment ctDNA can forecast real-time recurrence risk, facilitating risk-adapted, individualized patient management.

Breast cancer (BC) remains a significant global health concern, with neoadjuvant chemotherapy (NACT) offering preoperative benefits like tumor downstaging and treatment response assessment. However, identifying factors influencing post-NACT treatment response and survival outcomes is challenging. Metabolomic approaches offer promising insights into understanding these outcomes. This study analyzed the serum of 80 BC patients before and after NACT, followed for up to five years, correlating with disease-free survival (DFS) and overall survival (OS). Using untargeted nuclear magnetic resonance (NMR) spectroscopy and a novel statistical model that avoids collinearity issues, we identified metabolic changes associated with survival outcomes. Four metabolites (histidine, lactate, serine, and taurine) were significantly associated with DFS. We developed a metabolite-related survival score (MRSS) from these metabolites, stratifying patients into low- and high-risk relapse groups, independent of classical prognostic factors. High-risk patients had a hazard ratio (HR) for DFS of 3.42 (95% CI 1.51-7.74; p = 0.003) after adjustment for disease stage and age. A similar trend was observed for OS (HR of 3.34, 95% CI 1.64-6.80; p < 0.001). Multivariate Cox proportional hazards analysis confirmed the independent prognostic value of the MRSS. Our findings suggest the potential of metabolomic data, alongside traditional markers, in guiding personalized treatment decisions and risk stratification in BC patients undergoing NACT. This study provides a methodological framework for leveraging metabolomics in survival analyses.

Lymph node metastases are associated with poor prognosis in oral cavity squamous cell carcinoma (OCSCC). In other cancers, clinical guidelines on the number of lymph nodes removed during primary surgery, lymph node yield (LNY), exist. Here, we evaluated the prognostic capacity of LNY on regional failure, locoregional recurrence, and disease-free survival (DFS) in patients with OCSCC treated by primary neck surgery.

This retrospective cohort study took place at Sunnybrook Health Sciences Centre in Toronto, Canada and involved a chart review of all adult patients with treatment-naive OCSCC undergoing primary neck dissection. For each outcome, we first used the maximally selected rank statistics and an optimism-corrected concordance to identify an optimal threshold of LNY. We then used a multivariable Cox proportional hazards model to assess the association between high LNY (>threshold) and each outcome.

Among the 579 patients with OCSCC receiving primary neck dissection, 61.7% (n = 357) were male with a mean age of 62.9 years (standard deviation: 13.1) at cancer diagnosis. When adjusting for sociodemographic and clinical factors, LNY >15 was significantly associated with improved DFS (adjusted HR [aHR]: 0.73, 95% CI: 0.54-0.98), locoregional recurrence (aHR: 0.68, 95% CI: 0.49-0.95), and regional failure (aHR: 0.61, 95% CI: 0.39-0.93).

Our study findings suggested high LNY to be a strong independent predictor of various patient-level quality of surgical care metrics. The optimal LNY we found (15) was lower than the conventionally recommended (18), which calls for further research to establish validity in practice.