Conventional Prognostic Factors Research Articles

Large Scale Comparative Analysis of Canine and Human Osteosarcomas Uncovers Conserved Clinically Relevant Tumor Microenvironment Subtypes.

Osteosarcoma is an aggressive bone cancer lacking robust biomarkers for personalized treatment. Despite its scarcity in humans, it is relatively common in adult pet dogs. This study aimed to analyze clinically annotated bulk tumor transcriptomic datasets of canine and human osteosarcoma patients to identify potentially conserved patterns of disease progression. Bulk transcriptomic data from 245 pet dogs with treatment-naïve appendicular osteosarcoma were analyzed using deconvolution to characterize the tumor microenvironment (TME). The TME of both primary and metastatic tumors derived from the same dog was compared, and its impact on canine survival was assessed. A machine learning model was developed to classify the TME based on its inferred composition using canine tumor data. This model was applied to 8 independent human osteosarcoma datasets to assess its generalizability and prognostic value. This study found three distinct TME subtypes of canine osteosarcoma based on cell type composition of bulk tumor samples: Immune Enriched (IE), Immune Enriched Dense Extra-Cellular Matrix-like (IE-ECM), and Immune Desert (ID). These three TME-based subtypes of canine osteosarcomas were conserved in humans and could predict progression-free survival outcomes of human patients, independent of conventional prognostic factors such as percent tumor necrosis post standard of care chemotherapy treatment and disease stage at diagnosis. These findings demonstrate the potential of leveraging data from naturally occurring cancers in canines to model the complexity of the human osteosarcoma TME, offering a promising avenue for the discovery of novel biomarkers and developing more effective precision oncology treatments.

Response to induction chemotherapy modifies the effect of conventional prognostic factors in high-risk neuroblastoma: A report from the Children’s Oncology Group

BackgroundResponse to induction chemotherapy has been shown to predict outcome in patients with high-risk neuroblastoma (HR-NB), with those achieving a complete response (CR) having superior outcomes. MethodsWe evaluated whether conventional prognostic factors remain prognostic in subsets of patients defined by response to induction. 1244 Patients from four COG high-risk trials were included. End-induction response was coded as CR, partial response (PR) or better, less than PR without progressive disease (PD), and PD. Cox regression models were performed to calculate event-free and overall survival (EFS, OS) hazard ratios, including interaction terms between induction response and prognostic factors including sex, age, stage, primary tumor location, LDH, ferritin, ploidy, MYCN status, ALK status, histology, MKI, grade, and study era. ResultsAmong patients who achieved a CR after induction, INSS stage 4 disease and trial era were the only factors that remained significantly associated with inferior OS. For those who achieved less than a PR, adrenal primary site, MYCN amplification, and 1p LOH were associated with inferior outcomes. Multivariable models showed that end-induction response remained prognostic of EFS and OS even after controlling for other factors. Multiple significant statistical interactions were observed between end-induction response and other prognostic factors. ConclusionThe impact of conventional prognostic factors is not static in patients with HR-NB. Instead, response to induction chemotherapy modifies the effect of conventional prognostic factors. These data can help to further refine prognosis for patients with variable responses to induction and help to identify candidates who might benefit from treatment other than standard post-induction therapy.

Prognosis of primary breast salivary gland-type carcinoma: a propensity score-matching analysis with invasive carcinoma of no special type based on the SEER database for years 2010-2020.

Primary breast salivary gland-type carcinoma has weak evidence to support its management due to its rare occurrence and limited data regarding its clinicopathological features and prognosis. Therefore, this study aimed to assess clinicopathological features and prognosis for this type of carcinoma diagnosed over the past decade and compared those to the common breast invasive carcinoma of no special type (NST). This study used the Surveillance, Epidemiology, and End Results (SEER) database to extract data regarding primary breast salivary gland-type carcinoma. Using a propensity score-matching approach, the prognosis was compared with invasive carcinoma, NST. This study included 488 cases of salivary gland-type carcinoma and 375,660 cases of invasive carcinoma, NST, giving an occurrence ratio of 1 to 770. Adenoid cystic carcinoma (81%) formed the majority of salivary gland-type carcinoma, followed by secretory carcinoma (13%). For salivary gland-type carcinoma, acinic cell carcinoma histological type, tumor grade 3, HER2-overexpressed status, and higher AJCC stage groups were significant worse prognostic factors for breast cancer-specific survival in univariate analyses (p < 0.05). Nonetheless, tumor grade 3 and higher AJCC stage groups remained as significant independent prognostic factors in multivariate analysis (p < 0.05). The apparent better breast cancer-specific survival of salivary gland-type carcinoma as compared to that of invasive carcinoma, NST, was diminished following adjustment for differences in baseline clinicopathological features and treatment-related variables. This study suggests that when managing primary breast salivary gland-type carcinoma, greater emphasis should be given to the tumor grade and AJCC stage group in addition to acinic cell carcinoma histological type and HER2 overexpression. Conventional prognostic factors are important as salivary gland-type carcinoma had similar prognosis as invasive carcinoma, NST, following adjustment for confounding variables.

Abstract 7663: Identification of high-risk patients in multiple myeloma using a clonal gene signature

Abstract Introduction: Multiple myeloma (MM) is a heterogeneous disease with a small subset of high-risk patients associated with poor prognosis. The identification of these patients is crucial for treatment management and strategic decisions. Methods: We developed a novel computational framework that only requires gene expression profiles to define prognostic gene signatures by selecting genes with expression driven by inferred clonal copy number alterations. We applied this framework to MM and developed a clonal gene signature (CGS) consisting of only 22 genes. This prognostic signature was evaluated in 5 independent datasets with gene expression data of a total of 2,155 MM samples. For each patient, we calculated a prognostic score based on the expression of the signature genes. Multivariate Cox regression analyses were performed to investigate the association of these signature scores with patient prognosis after adjusting established clinical factors. The performances of CGS and the only commercialized MM gene signatures, GEP70 and SKY92, in identifying high-risk patients were carefully compared by multiple different approaches. Results: Our results indicated that CGS provided significant prognostic values after adjusting for well-established prognostic factors including cytogenetic abnormalities, International Staging System (ISS), and Revised ISS (R-ISS). In addition, it showed significant prognostic associations in patient subsets stratified by these conventional prognostic factors. Importantly, CGS demonstrated a better performance in identifying high-risk patients compared to the GEP70 and SKY92 signatures, which have been recommended for prognostic stratification in MM. Moreover, CGS can further stratify patients into subgroups with significantly differential prognoses when applied to the high-risk and low-risk groups already identified by GEP70 and SKY92. The higher CGS score of patients is significantly associated with poor response to dexamethasone, a commonly used drug for MM treatment. Conclusions: In summary, we proposed a computational framework that only requires gene expression data to identify clonal gene signatures for prognosis prediction. The CGS provides a useful biomarker for improving prognostic stratification in MM, especially for the identification of patients with the highest risk. The computational framework used for defining this signature provides a useful tool, which can be readily applied to many other cancer types. Citation Format: Jian-Rong Li, Christiana Wang, Chao Cheng. Identification of high-risk patients in multiple myeloma using a clonal gene signature [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7663.

High-Serum Brain-Derived Neurotrophic Factor Levels Are Associated With Decreased Risk of Poststroke Cognitive Impairment.

BDNF (brain-derived neurotrophic factor) is widely implicated in the pathophysiological process of stroke, but the effect of BDNF on poststroke cognitive impairment (PSCI) remains unclear. We aimed to investigate the association between baseline serum BDNF and the risk of PSCI at 3 months in a multicenter study based on a preplanned ancillary study of the CATIS trial (China Antihypertensive Trial in Acute Ischemic Stroke). We examined serum BDNF levels at baseline and used the Mini-Mental State Examination and Montreal Cognitive Assessment to evaluate cognitive function at 3-month follow-up after ischemic stroke. PSCI was defined as Mini-Mental State Examination score <27 or Montreal Cognitive Assessment score <25. Logistic regression analyses were performed to evaluate the association between serum BDNF and the risk of 3-month PSCI. In this ancillary study, a total of 660 patients with ischemic stroke with hypertension were included, and 593 patients (mean age, 59.90±10.44 years; 410 males and 183 females) were finally included in this analysis. According to mini-mental state examination score, after adjustment for age, sex, education, baseline National Institutes of Health Stroke Scale score, APOE ɛ4 carriers, and other potential confounders, the odds ratio of PSCI for the highest tertile of BDNF was 0.60 ([95% CI, 0.39-0.94]; P=0.024) compared with the lowest tertile. Multiple-adjusted spline regression model showed a linear association of serum BDNF levels with PSCI at 3 months (P value for linearity=0.010). Adding serum BDNF to conventional prognostic factors slightly improved the risk reclassification of PSCI (net reclassification improvement: 27.46%, P=0.001; integrated discrimination index: 1.02%, P=0.015). Similar significant findings were observed when PSCI was defined by the Montreal Cognitive Assessment score. Elevated serum BDNF levels were associated with a decreased risk of PSCI at 3 months, suggesting that serum BDNF might be a potential predictive biomarker for PSCI among patients with ischemic stroke with hypertension.

Abstract C030: Serum levels and tumor tissue organization of decorin in pancreatic cancer: Links to chemoresistance and disease aggressiveness

Abstract Pancreatic cancer has nearly paralleling incidence and mortality rates. Only 15-20% of the tumors are resectable at presentation, and for the majority of patients the situation is palliative. Treatment options are limited to standard chemotherapy, and tumor response is often transient. The longitudinal observational clinical study Chemotherapy, Host response And Molecular dynamics in Periampullary cancer (CHAMP) aims to contribute with new insights on this devastating disease through longitudinal blood sampling during adjuvant and palliative chemotherapy and comprehensive analysis of tissue from resected as well as postmortem sampled tumor tissue. In the present study, encompassing the first 100 patients enrolled in the CHAMP study, 92 serum proteins related to inflammation and cancer were analyzed by proximity extension assay in on-treatment blood samples from baseline to six months. The results revealed that the small leucin-rich proteoglycan decorin was among the top up-regulated proteins during chemotherapy. After three months of treatment, high levels of serum decorin were significantly associated with a shorter overall survival (log rank p = 0.005). Decorin expression was also assessed by immunohistochemistry in resected tumors from 25 patients and in postmortem sampled primary tumors and metastases from 9 patients. In the latter, particularly strong expression of decorin, both in the tumor cells and in the stroma, was denoted in cases with a short overall survival. While there was no significant correlation between decorin in the tumors and in serum at baseline, strong correlations were seen at one and three months (Spearman’s rho = 0.70 and 0.85, respectively). To further validate the potential prognostic value of decorin, immunohistochemical analysis was performed on tumors from a retrospective cohort of 104 resected tumors with long-term follow-up. Survival analysis showed that high decorin expression in both the stromal compartment and in tumor cells was associated with shorter overall survival (log rank p = 0.036 and 0.001, respectively). Multivariable cox regression analysis, adjusted for conventional prognostic factors, further confirmed that decorin was an independent factor of shorter overall survival (hazard ratio: 1.74, 95% confidence interval 1.10-2.75 for stromal decorin, and hazard ratio: 1.83, 95% confidence interval 1.04-3.21 for tumor-cell specific decorin). In conclusion, these findings suggest that decorin may be associated with chemotherapy resistance in pancreatic cancer. Future studies are encouraged to further explore the mechanistic basis for these observations, and to validate the potential utility of serum-decorin as a biomarker to monitor treatment response. Citation Format: Maja Svensson, Johan Ohlsson, Sofie Olsson Hau, Alexandra Petersson, Karin Jirström. Serum levels and tumor tissue organization of decorin in pancreatic cancer: Links to chemoresistance and disease aggressiveness [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C030.

Intratumoral heterogeneity of Ki67 proliferation index outperforms conventional immunohistochemistry prognostic factors in estrogen receptor-positive HER2-negative breast cancer.

In breast cancer (BC), pathologists visually score ER, PR, HER2, and Ki67 biomarkers to assess tumor properties and predict patient outcomes. This does not systematically account for intratumoral heterogeneity (ITH) which has been reported to provide prognostic value. This study utilized digital image analysis (DIA) and computational pathology methods to investigate the prognostic value of ITH indicators in ER-positive (ER+) HER2-negative (HER2-) BC patients. Whole slide images (WSIs) of surgically excised specimens stained for ER, PR, Ki67, and HER2 from 254 patients were used. DIA with tumor tissue segmentation and detection of biomarker-positive cells was performed. The DIA-generated data were subsampled by a hexagonal grid to compute Haralick's texture indicators for ER, PR, and Ki67. Cox regression analyses were performed to assess the prognostic significance of the immunohistochemistry (IHC) and ITH indicators in the context of clinicopathologic variables. In multivariable analysis, the ITH of Ki67-positive cells, measured by Haralick's texture entropy, emerged as an independent predictor of worse BC-specific survival (BCSS) (hazard ratio (HR) = 2.64, p-value = 0.0049), along with lymph node involvement (HR = 2.26, p-value = 0.0195). Remarkably, the entropy representing the spatial disarrangement of tumor proliferation outperformed the proliferation rate per se established either by pathology reports or DIA. We conclude that the Ki67 entropy indicator enables a more comprehensive risk assessment with regard to BCSS, especially in cases with borderline Ki67 proliferation rates. The study further demonstrates the benefits of high-capacity DIA-generated data for quantifying the essentially subvisual ITH properties.

Novel biomarker SARIFA in colorectal cancer: highly prognostic, not genetically driven and histologic indicator of a distinct tumor biology

SARIFA (Stroma AReactive Invasion Front Areas) has recently emerged as a promising histopathological biomarker for colon and gastric cancer. To elucidate the underlying tumor biology, we assessed SARIFA-status in tissue specimens from The-Cancer-Genome-Atlas (TCGA) cohorts COAD (colonic adenocarcinoma) and READ (rectal adenocarcinoma). For the final analysis, 207 CRC patients could be included, consisting of 69 SARIFA-positive and 138 SARIFA-negative cases. In this external validation cohort, H&E-based SARIFA-positivity was strongly correlated with unfavorable overall, disease-specific, and progression-free survival, partly outperforming conventional prognostic factors. SARIFA-positivity was not associated with known high-risk genetic profiles, such as BRAF V600E mutations or microsatellite-stable status. Transcriptionally, SARIFA-positive CRCs exhibited an overlap with CRC consensus molecular subtypes CMS1 and CMS4, along with distinct differential gene expression patterns, linked to lipid metabolism and increased stromal cell infiltration scores (SIIS). Gene-expression-based drug sensitivity prediction revealed a differential treatment response in SARIFA-positive CRCs. In conclusion, SARIFA represents the H&E-based counterpart of an aggressive tumor biology, demonstrating a partial overlap with CMS1/4 and also adding a further biological layer related to lipid metabolism. Our findings underscore SARIFA-status as an ideal biomarker for refined patient stratification and novel drug developments, particularly given its cost-effective assessment based on routinely available H&E slides.

Clinical Significance of Measurable Residual Disease (MRD) in Relapsed/Refractory Multiple Myeloma (RRMM) Patients (Pts) Treated with Chimeric Antigen Receptor (CAR) T Cells and T-Cell Engagers (TCE)

Clinical Significance of Measurable Residual Disease (MRD) in Relapsed/Refractory Multiple Myeloma (RRMM) Patients (Pts) Treated with Chimeric Antigen Receptor (CAR) T Cells and T-Cell Engagers (TCE)

Peak early diastolic strain rate improves prediction of adverse cardiovascular outcomes in patients with ST-elevation myocardial infarction.

The prognostic role of diastolic dysfunction measured by the circumferential peak early diastolic strain rate (PEDSR) on ST-elevation myocardial infarction (STEMI) is not completely established. We aimed to investigate the prognostic value of diastolic function by measuring PEDSR within 1week after STEMI. The cardiac magnetic resonance (CMR) pictures of 420 subjects from a clinical registry study (NCT03768453) were analyzed and the composite major adverse cardiac events (MACEs) were followed up. The PEDSR of patients was significantly lower compared with that of control subjects (P < 0.001). Within the median follow-up period of 52months, PEDSR of patients who experienced MACEs deceased more significantly than that of patients without MACEs (P < 0.001). After adjusting with clinical or CMR indexes, per 0.1/s reduction of PEDSR increased the risks of MACEs to 1.402 or 1.376 fold and the risk of left ventricular (LV) remodeling to 1.503 or 1.369 fold. When PEDSR divided by best cutoff point, significantly higher risk of MACEs (P < 0.001) and more remarkable LV remodeling (P < 0.001) occurred in patients with PEDSR ≤ 0.485/s. Moreover, when adding the PEDSR to the conventional prognostic factors such as LV ejection fraction and infarction size, better prognostic risk classification models were created. Finally, aging, tobacco use, remarkable LV remodeling, and a low LV ejection fraction were factors related with the reduction of PEDSR. Diastolic dysfunction has an important prognostic effect on patients with STEMI. Measurement of the PEDSR in the acute phase could serve as an effective index to predict the long-term risk of MACEs and cardiac remodeling.

Deep learning approach for analyzing chest x-rays to predict cardiac events in heart failure.

A deep learning (DL) model based on a chest x-ray was reported to predict elevated pulmonary artery wedge pressure (PAWP) as heart failure (HF). The aim of this study was to (1) investigate the role of probability of elevated PAWP for the prediction of clinical outcomes in association with other parameters, and (2) to evaluate whether probability of elevated PAWP based on DL added prognostic information to other conventional clinical prognostic factors in HF. We evaluated 192 patients hospitalized with HF. We used a previously developed AI model to predict HF and calculated probability of elevated PAWP. Readmission following HF and cardiac mortality were the primary endpoints. Probability of elevated PAWP was associated with diastolic function by echocardiography. During a median follow-up period of 58 months, 57 individuals either died or were readmitted. Probability of elevated PAWP appeared to be associated with worse clinical outcomes. After adjustment for readmission score and laboratory data in a Cox proportional-hazards model, probability of elevated PAWP at pre-discharge was associated with event free survival, independent of elevated left atrial pressure (LAP) based on echocardiographic guidelines (p < 0.001). In sequential Cox models, a model based on clinical data was improved by elevated LAP (p = 0.005), and increased further by probability of elevated PAWP (p < 0.001). In contrast, the addition of pulmonary congestion interpreted by a doctor did not statistically improve the ability of a model containing clinical variables (compared p = 0.086). This study showed the potential of using a DL model on a chest x-ray to predict PAWP and its ability to add prognostic information to other conventional clinical prognostic factors in HF. The results may help to enhance the accuracy of prediction models used to evaluate the risk of clinical outcomes in HF, potentially resulting in more informed clinical decision-making and better care for patients.

Genetic alterations in peritoneal metastatic tumors predicted the outcomes for hyperthermic intraperitoneal chemotherapy.

Cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) are considered for patients with peritoneal metastasis (PM). However, patients selection that relies on conventional prognostic factors is not yet optimal. In this study, we performed whole exome sequencing (WES) to establish tumor molecular characteristics and expect to identify prognosis profiles for PM management. In this study, blood and tumor samples were collected from patients with PM before HIPEC. Tumor molecular signatures were determined using WES. Patient cohort was divided into responders and non-responders according to 12-month progression-free survival (PFS). Genomic characteristics between the two cohorts were compared to study potential targets. In total, 15 patients with PM were enrolled in this study. Driver genes and enriched pathways were identified from WES results. AGAP5 mutation was found in all responders. This mutation was significantly associated with better OS (p = 0.00652). We identified prognostic markers that might be useful to facilitate decision-making before CRS/HIPEC.

Cell-free DNA as a prognostic and predictive biomarker in resectable distal common bile duct cancer.

Cell-free DNA (cfDNA) as an oncological biomarker has drawn much attention in recent years, but very limited effort has been made to investigate the prognostic values of cfDNA in distal common bile duct (CBD) cancer. Plasma cfDNA was measured in 67 patients with resectable distal CBD cancer. Survival outcomes and the correlation of cfDNA with other conventional prognostic factors were determined. cfDNA levels were significantly higher in female patients, and those with poor tumor differentiation, abnormal serum carcinoembryonic antigen (CEA) level, and stage III cancer. The significant prognostic factors included a high cfDNA level (>8955 copies/mL), abnormal serum CEA level, stage III cancer, and positive resection margins. Compared with patients with high cfDNA level, those with lower cfDNA level (≤8955 copies/mL) had significantly better overall survival outcomes (74.4% vs 100% and 19.2% vs 52.6%, for 1- and 5-year survival rates, respectively, p = 0.001). The cfDNA level, perineural invasion, CEA level, and radicality were identified as independent prognostic factors for distal CBD cancer after multivariate analysis. Circulating cfDNA levels play a significant role in predicting the prognosis and survival outcome for resectable distal CBD cancer. Furthermore, acting as a promising liquid biopsy, cfDNA could serve as a prognostic and predictive biomarker in combination with current conventional markers to improve diagnostic and prognostic efficacy.

Zeta-associated protein 70 expression in chronic lymphocytic leukemia: Relevance in Indian context.

Chronic lymphocytic leukemia (CLL) is prognosticated using the Rai and the Binet's staging. In the past few years, new parameters have been considered for prognostication. One such marker that has been a subject of speculation and found useful by some western studies is zeta-associated protein 70 (ZAP-70). To investigate the prevalence of ZAP-70 and find out its association with other prognostic markers like Rai and Binet's stage and CD38 in Indian CLL patients. Twenty-nine newly diagnosed cases of CLL were selected over 1 year. Immunophenotyping was done and expression of CD38 and ZAP-70 was evaluated on gated CLL cells. Qualitative data were expressed as frequency and percentage. Differences between groups were evaluated using Student's t-test for quantitative data and Chi-square test/Fisher's exact t-test for qualitative variables. A P value less than 0.05 was considered significant. We found a lower prevalence rate of ZAP-70 (2/29, 6.89%) with no association with any of the conventional poor prognostic factors. A large number of our CLL patients fall into the good prognostic group (22/29, ZAP 70-/CD38-) with a least number in the poor prognostic group (2/29, ZAP-70 + CD38+). Also, no association was found between ZAP-70 and CD38. The findings of the present study suggest that the majority of CLL patients in India have a good prognosis, may not require treatment, and have good overall survival. Geographical variations, genetic makeup, and natural history of the CLL could be the cause of such differences from western literature.

Lipid biomarkers that reflect postoperative recurrence risk in lung cancer patients who smoke: a case–control study

BackgroundThe risk of postoperative recurrence is higher in lung cancer patients who smoke than non-smokers. However, objective evaluation of the postoperative recurrence risk is difficult using conventional pathological prognostic factors because of their lack of reproducibility. Consequently, novel objective biomarkers that reflect postoperative risk in lung cancer patients who smoke must be identified. Because cigarette smoking and oncogenesis alter lipid metabolism in lung tissue, we hypothesized that the lipid profiles in lung cancer tissues are influenced by cigarette smoking and can reflect the postoperative recurrence risk in smoking lung cancer patients. This study aimed to identify lipid biomarkers that reflect the smoking status and the postoperative recurrence risk.MethodsPrimary tumor tissues of lung adenocarcinoma (ADC) (n = 26) and squamous cell carcinoma (SQCC) (n = 18) obtained from surgery were assigned to subgroups according to the patient’s smoking status. The ADC cohort was divided into never smoker and smoker groups, while the SQCC cohort was divided into moderate smoker and heavy smoker groups. Extracted lipids from the tumor tissues were subjected to liquid chromatography-tandem mass spectrometry analysis. Lipids that were influenced by smoking status and reflected postoperative recurrence and pathological prognostic factors were screened.ResultsTwo and 12 lipid peaks in the ADC and SQCC cohorts showed a significant positive correlation with the Brinkman index, respectively. Among them, in the ADC cohort, a higher lipid level consisted of three phosphatidylcholine (PC) isomers, PC (14:0_18:2), PC (16:1_16:1), and PC (16:0_16:2), was associated with a shorter recurrence free period (RFP) and a greater likelihoods of progressed T-factor (≥ pT2) and pleural invasion. In the SQCC cohort, a lower m/z 736.5276 level was associated with shorter RFP and greater likelihood of recurrence.ConclusionsFrom our data, we propose three PC isomers, PC (14:0_18:2), PC (16:1_16:1), and PC (16:0_16:2), and a lipid peak of m/z 736.5276 as novel candidate biomarkers for postoperative recurrence risk in lung ADC and SQCC patients who are smokers.

Immune Biomarkers of Survival and Severe Infection in Newly Diagnosed Multiple Myeloma (NDMM) Patients (pts) Treated with the Backbone Regimen Lenalidomide and Dexamethasone (Rd)

Introduction: Rd is a backbone of treatment in MM. The strong immunomodulatory effects of this regimen would suggest that immune profiling might complement conventional prognostic factors. However, immune signatures predictive of survival were not well defined in the past, and nowadays it is challenging to detach the effect of Rd from other backbone drugs in triplets or quadruplets, as well from high dose therapy in transplant eligible patients. Aim: Identify immune biomarkers in elderly NDMM pts treated with Rd. Methods: The GEM-CLARIDEX trial randomized transplant ineligible NDMM pts to Rd +/- clarithromycin until disease progression. Because clarithromycin had no effect in survival, the trial design yielded a unique opportunity to identify immune biomarkers in elderly MM pts treated with Rd. Immune profiling was performed in bone marrow (BM) at baseline in 186 pts, using multidimensional and computational flow cytometry together with lasso penalized Cox regression and 10-fold cross validation, for a holistic and unbiased definition of prognostic immune signatures. 38 cell populations were identified, including seven myeloid/erythroid and 29 lymphoid subsets plus normal and clonal plasma cells (PC). Single cell RNA sequencing (scRNAseq, 10x Genomics) was performed on BM immune cells sorted from healthy adults, MGUS, smoldering and active MM pts (n = 17). Results: An immune signature associated with inferior survival was defined based on increased frequency of cytotoxic CD314+ NK and CD4+ central memory (CM) CD127+ PD1+ T cells, and decreased percentages of CD4+ CM CD127+ PD1- and CD8+ CD127low PD1+ terminally differentiated T cells, as well as of B cell precursors. Median progression-free survival (PFS) of NDMM pts with high risk immune score (106/186 [57%]) was 18 months vs not reached in those with low risk (80/186 [43%]) (p=.0008, Fig 1A). The respective median overall survival (OS) rates at three years were 50% and 80% (p = .0021, Fig 1B). In multivariate analyses including age, ISS, LDH and cytogenetic risk, immune profiling showed independent prognostic value for PFS (HR: 2.6, p = .001) and OS (HR: 2.9, p = .003). Increased frequency of cytotoxic CD314+ NK cells was the immune biomarker with the highest negative impact in the survival predictive model. In an attempt to better understand this finding, we analyzed scRNAseq data of 61,637 NK cells from normal and tumor BM. Up to 47 NK-cell clusters were identified, and the one showing the highest expression of CD314 also displayed upregulation of granzymes K, H and B, perforin, CD16, CD38, CD69 and IFNγ, and therefore appeared to be associated with cytolytic activity and inflammation. Interestingly, there was a progressive expansion of this cluster within the NK cell compartment of normal vs pre-malignant vs neoplastic BM samples. Similarly, in genetically engineered BIcγ1 mice that develop active MM preceded by precursor states, there was a progressive expansion of CD314+ NK cells in normal vs benign vs malignant BM (p = .001). Being infection an important cause of morbidity and mortality in elderly MM pts as those included in this study, we next investigated if immune profiling at diagnosis could help predicting severe infection (≥ grade 3 CTCAE v4.0, n=43/186). The combination of five clinical features - age ≥ 75y, low hemoglobin and albumin, high β2m and LDH - plus seven immune biomarkers - increased percentages of eosinophils, together with decreased frequencies of CD4+ CM CD127+ PD1-, CD8+ naïve and CD127low PD1+ and PD1- terminally differentiated T cells, B cell precursors and normal PC - resulted in the most effective model to predict severe infection. B cell precursors and eosinophils, which are easily identified using flow cytometry at diagnosis, showed the strongest association. The area under the curve (AUC) of the model was 0.90 with a 4-fold cross validation showing a mean AUC = 0.86 ± 0.06. Conclusions: This study shows the clinical value of immune profiling at diagnosis and defined immune cell types, including a previously unidentified subset of CD314+ cytotoxic NK cells, which were predictive of survival in transplant ineligible NDMM pts treated with the backbone regimen Rd. Furthermore, this study uncovered immune biomarkers complementary to clinical features for predicting severe infection in elderly MM pts, which could be used to intensify prophylactic measures in specific subgroups that are more susceptible to severe infection. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Abstract 14409: Deep Learning Approach for Analyzing Chest X-rays to Predict Cardiac Events in Heart Failure

Introduction: A deep learning (DL) model based on a chest X-ray (CXR) was reported to predict elevated pulmonary artery wedge pressure (PAWP) as congestive heart failure (HF). Hypothesis: We hypothesize that a previously developed application of a CXR-based DL algorithm could also be used to predict re-hospitalized HF in patients with HF. This study aimed to 1) investigate the role of probability of elevated PAWP to predict clinical outcomes in association with other parameters, and 2) to evaluate whether probability of elevated PAWP based on DL added prognostic information to other conventional clinical prognostic factors in HF. Methods: We evaluated 192 patients hospitalized with HF. We used a previously developed AI model to predict HF and calculated probability of elevated PAWP in the study cohort. The primary endpoint was readmission following HF and cardiac death. Results: Probability of elevated PAWP was associated with echocardiographic parameters including left atrial size, filling pressure, and pulmonary artery pressure. During a median follow-up period of 58 months, 57 patients were either readmitted or died. Probability of elevated PAWP appeared to be associated with worse clinical outcomes. After adjustment for readmission score and laboratory data in a Cox proportional-hazards model, probability of elevated PAWP at pre-discharge (per 1SD) was associated with event free survival, independent of elevated left atrial pressure (LAP) by echocardiography (hazard ratio:1.39, 95%CI:1.17-1.65, p&lt;0.001). In sequential Cox models, a model based on clinical data (χ2, 16.8) was improved by elevated LAP (χ2,24.4; p =0.005), and increased further by probability of elevated PAWP (χ2,41.1; p &lt;0.001). Conclusions: This study suggests that probability of elevated PAWP provides important incremental prognostic value for predicting readmission and cardiac mortality risk assessment in patients with HF.

Tertiary lymphoid structures associate with improved survival in early oral tongue cancer

BackgroundThe clinical significance of tertiary lymphoid structures (TLSs) is not well-documented in early oral tongue squamous cell carcinoma (OTSCC).MethodsA total of 310 cases of early (cT1-2N0) OTSCC were included in this multicenter study. Assessment of TLSs was conducted on hematoxylin and eosin-stained sections. TLSs were assessed both in the central part of the tumor and at the invasive front area.ResultsThe presence of TLSs associated with improved survival of early OTSCC as presented by Kaplan–Meier survival analyses for disease-specific survival (P = 0.01) and overall survival (P = 0.006). In multivariable analyses, which included conventional prognostic factors, the absence of TLSs associated with worse disease-specific survival with a hazard ratio (HR) of 1.96 (95% CI 1.09–3.54; P = 0.025) and poor overall survival (HR 1.66, 95% CI 1.11–2.48; P = 0.014).ConclusionHistological evaluation of TLSs predicts survival in early OTSCC. TLSs showed superior prognostic power independent of routine WHO grading and TNM staging system.

Influence of anesthetic technique on survival after tumor debulking surgery of elderly patients with ovarian cancer: Results of a retrospective cohort study.

Epidural analgesia could influence the postoperative oncologic outcomes in patients with specific types of non-metastatic solid neoplasms. The present study aimed to investigate the impact of anesthetic technique on survival in elderly patients with ovarian cancer (OC). The records of all women with OC older than 60 years of age undergoing tumor debulking surgery at the University Medical Center of the Johannes Gutenberg University Mainz (Mainz, Germany) between January 2008 and December 2019 were obtained. The study cohort was divided into two groups based on the use of perioperative epidural anesthesia or not. First, Kaplan-Meier analysis was performed to analyze the prognostic influence of anesthetic technique on survival. Second, multivariate Cox proportional hazards model was adjusted for multiple conventional prognostic factors concerning three main categories: i) Current clinical-pathological tumor characteristics; ii) anesthesiologic parameters, including mean age, American Society of Anesthesiologists Performance Status and preexisting comorbidities summarized in the Charlson Comorbidity Index; and iii) oncological and surgical parameters such as oncological radicality and Surgical complexity Score. A total of 110 patients were included in the study and 71 (64.5%) of them received epidural analgesia. The median survival time was 26.0 months from primary debulking surgery and no significant differences in progression-free (PFS) and overall survival (OS) were noted between the ‘Epidural’ and ‘non-Epidural’ cohorts. After adjustment for the selected risk factors from the three categories, the effects of epidural analgesia on PFS and OS remained non-significant [PFS: hazard ratio (HR), 1.26; 95% CI, 0.66–2.39; and OS: HR, 0.79; 95% CI, 0.45–1.40]. The present results did not support the independent association between epidural-supplemented anesthesia and improved PFS or OS in elderly patients with standardized ovarian cancer debulking surgery.

Incremental Value of Radiomics in 5-Year Overall Survival Prediction for Stage II-III Rectal Cancer.

Although rectal cancer comprises up to one-third of colorectal cancer cases and several prognosis nomograms have been established for colon cancer, statistical tools for predicting long-term survival in rectal cancer are lacking. In addition, previous prognostic studies did not include much imaging findings, qualitatively or quantitatively. Therefore, we include multiparametric MRI information from both radiologists’ readings and quantitative radiomics signatures to construct a prognostic model that allows 5-year overall survival (OS) prediction for advance-staged rectal cancer patients. The result suggested that the model combined with quantitative imaging findings might outperform that of conventional TNM staging or other clinical prognostic factors. It was noteworthy that the identified radiomics signature consisted of three from dynamic contrast-enhanced (DCE)-MRI, four from anatomical MRI, and one from functional diffusion-weighted imaging (DWI). This highlighted the importance of multiparametric MRI to address the issue of long-term survival estimation in rectal cancer. Additionally, the constructed radiomics signature demonstrated value to the conventional prognostic factors in predicting 5-year OS for stage II–III rectal cancer. The presented nomogram also provides a practical example of individualized prognosis estimation and may potentially impact treatment strategies.