Pre-treatment serum lactate dehydrogenase as a biomarker in small cell lung cancer

Novel prediction model of early screening lung adenocarcinoma with pulmonary fibrosis based on haematological index

BACKGROUND

Lung cancer (LC), a paramount global life-threatening condition causing significant mortality, is most commonly characterized by its subtype, lung adenocarcinoma (LUAD). Concomitant with LC, pulmonary fibrosis (PF) and interstitial lung disease (ILD) contribute to an intricate landscape of respiratory diseases. Idiopathic pulmonary fibrosis (IPF) in association with LC has been explored. However, other fibrotic interrelations remain underrepresented, especially for LUAD-PF and LUAD-ILD.

METHODS

We analysed data with statistical analysis from 7,137 healthy individuals, 7,762 LUAD patients, 7,955 ILD patients, and 2,124 complex PF patients collected over ten years. Furthermore, to identify blood indicators related to lung disease and its complications and compare the relationships between different indicators and lung diseases, we successfully applied the naive Bayes model for a biomarker-based prediction of diagnosis and development into complex PF.

RESULTS

Males predominantly marked their presence in all categories, save for complex PF where females took precedence. Biomarkers, specifically AGR, MLR, NLR, and PLR emerged as pivotal in discerning lung diseases. A machine-learning-driven predictive model underscored the efficacy of these markers in early detection and diagnosis, with NLR exhibiting unparalleled accuracy.

CONCLUSIONS

Our study elucidates the gender disparities in lung diseases and illuminates the profound potential of serum biomarkers, including AGR, MLR, NLR, and PLR in early lung cancer detection. With NLR as a standout, therefore, this study advances the exploration of indicator changes and predictions in patients with pulmonary disease and fibrosis, thereby improving early diagnosis, treatment, survival rate, and patient prognosis.

Enzymes as indispensable markers in disease diagnosis

Enzymes have been used for disease diagnosis for many decades; however, advancements in technology like ELISA and flow cytometry-based detection have significantly increased their use and have increased the sensitivity of detection. Technological advancements in recombinant enzyme production have increased enzymatic stability, and the use of colorimetric-based and florescence-based assays has led to their increased use as biomarkers for disease detection. Enzymes like acid phosphatase, cathepsin, lactate dehydrogenase, thymidine kinase and creatine kinase are indispensable markers for diagnosing cancer, cardiovascular diseases and others. This minireview summarizes various enzymes used in disease diagnosis, their metabolic role, market value and potential as disease markers across various metabolic and other disorders.

Albumin‑bilirubin grade is an independent prognostic factor for small lung cell cancer

Albumin-bilirubin (ALBI) grade was first described in 2015 as an indicator of liver dysfunction in patients with hepatocellular carcinoma. ALBI grade has been reported to have prognostic value in several malignancies including non-small cell lung cancer (NSCLC). The present study aimed to explore the prognostic impact of ALBI grade in patients with small cell lung cancer (SCLC). It retrospectively analyzed 135 patients with SCLC treated at Hebei General Hospital between April 2015 and August 2021. Patients were divided into two groups according to the cutoff point of ALBI grade determined by the receiver operating characteristic (ROC) curve: Group 1 with pre-treatment ALBI grade ≤-2.55 for an improved hepatic reserve and group 2 with ALBI grade >-2.55. Kaplan-Meier and Cox regression analysis were performed to assess the potential prognostic factors associated with progression free survival (PFS) and overall survival (OS). Propensity score matching (PSM) was applied to eliminate the influence of confounding factors. PFS and OS (P<0.001) were significantly improved in group 1 compared with in group 2. Multivariate analysis revealed that sex (P=0.024), surgery (P=0.050), lactate dehydrogenase (LDH; P=0.038), chemotherapy (P=0.038) and ALBI grade (P=0.028) are independent risk factors for PFS and that surgery (P=0.013), LDH (P=0.039), chemotherapy (P=0.009) and ALBI grade (P=0.013) are independent risk factors for OS. After PSM, ALBI grade is an independent prognostic factor of PFS (P=0.039) and OS (P=0.007). It was concluded that ALBI grade was an independent prognostic factor in SCLC.

Clinicopathological Features and First-Line Treatment Outcomes of Geriatric Patients With Extensive-Stage Small Cell Lung Cancer: A Multicenter Study

Introduction The geriatric patient population diagnosed with extensive stage small cell lung cancer (SCLC) is underrepresented in clinical studies. We aimed to evaluate the clinicopathological characteristics, first-line treatment patterns and treatment outcomes of patients aged 65 years or older with extensive stage SCLC. Material and methods In this multicenter, retrospective cohort study, patients aged 65 years or older, diagnosed with extensive-stage SCLC, between January 2009 and December 2021 were included. Patients who were under 65 years of age at the time of diagnosis and did not develop progression after curative treatment and patients with a second malignancy were excluded from the study. The clinicopathological characteristics, first-line treatment patterns and treatment outcomes were analyzed. Results A total of 132 patients were included in the study. The median age was 70 years (range:65-91), and 118 (89.4%) patients were male. There were 77 (58.3%) patients with eastern cooperative oncology group (ECOG) performance status (PS) of 0-1. There were 26 (19.7%) patients in the limited stage disease and 106 (80.3%) patients in the extensive stage disease at the time of diagnosis. First-line chemotherapy was given to 86 (65.2%) patients. Of the patients who could not receive treatment, 18 patients (13.6%) due to patient refusal, and 28 patients (21.2%) due to comorbid diseases and poor performance status with organ dysfunctions. The most common treatment regimen used as first-line treatment was cisplatin+etoposide (n=47, 54.7%), and followed by carboplatin+etoposide (n=39, 45.3%). First-line chemotherapy responses were complete response in 4 (4.7%) patients, partial response in 35 (40.7%) patients, stable disease in 13 (15.1%) patients, and progressive disease in 34 (39.5%) patients. The most common grade 3-4 adverse events was neutropenia in 33 (38.4%) patients. Forty nine patients (57.0%) completed the planned first-line treatment. The mPFS was 6.1 months and the mOS was 8.2 months with first-line treatment. We found that ECOG PS status was the most important negative prognostic factor for both PFS and OS. There was no difference between carboplatin+etoposide and cisplatin+etoposide regimens in terms of PFS, OS, adverse events and treatment compliance. Conclusion Thus, it may be an appropriate approach not to give up chemotherapy treatment easily in elderly patients with a diagnosis of extensive stage SCLC. It should be kept in mind that finding factors that might affect the prognosis and tailoring the tretment precisely on case-by-case basis in geriatric cancer patients have an impact on survival.

Understanding the Contribution of Lactate Metabolism in Cancer Progress: A Perspective from Isomers

Lactate mediates multiple cell-intrinsic effects in cancer metabolism in terms of development, maintenance, and metastasis and is often correlated with poor prognosis. Its functions are undertaken as an energy source for neighboring carcinoma cells and serve as a lactormone for oncogenic signaling pathways. Indeed, two isomers of lactate are produced in the Warburg effect: L-lactate and D-lactate. L-lactate is the main end-production of glycolytic fermentation which catalyzes glucose, and tiny D-lactate is fabricated through the glyoxalase system. Their production inevitably affects cancer development and therapy. Here, we systematically review the mechanisms of lactate isomers production, and highlight emerging evidence of the carcinogenic biological effects of lactate and its isomers in cancer. Accordingly, therapy that targets lactate and its metabolism is a promising approach for anticancer treatment.

A composite indicator of derived neutrophil-lymphocyte ratio and lactate dehydrogenase correlates with outcomes in pancreatic carcinoma patients treated with PD-1 inhibitors

BACKGROUND

There are currently no established biomarkers that can predict whether advanced pancreatic carcinoma (PC) patients would benefit from immune checkpoint inhibitors (ICIs). Our study investigated whether the pretreatment composite biomarker of derived neutrophil-lymphocyte ratio (dNLR) and lactate dehydrogenase (LDH) can be used as a reliable prognostic factor for the survival of PC patients receiving PD-1 inhibitor therapy.

METHODS

Patients with advanced PC treated with PD-1 inhibitors at a single center from September 2015 to September 2020 were included. The high levels of dNLR (≥3) and LDH (≥250 U/L) were considered to be risk factors. Based on these two risk factors, patients in this study were categorized into two risk groups: the good dNLR-LDH group, without risk factors, and the intermediate/poor dNLR-LDH group, with one to two risk factors. Overall survival (OS) and progression-free survival (PFS) served as this study's primary and secondary endpoints. Cox regression models were used to identify independent prognostic factors for survival benefit.

RESULTS

There were 98 patients in our study. The good group included 61 (62.2%) patients and the intermediate/poor group included 37 (37.8%). The overall patients with PC who received immunotherapy had a median OS of 12.1 months, and the good dNLR-LDH group had a significantly longer OS compared with the intermediate/poor dNLR-LDH group (44.2 vs. 6.4 months; p < 0.010); median PFS was 3.7 and 2.5 months (p = 0.010). The number of metastatic sites >2 and immunotherapy as third-line or later was associated with worse PFS, and the line of immunotherapy and the dNLR-LDH indicator were independent prognostic factors for OS, according to multivariate analysis.

CONCLUSION

The pretreatment composite biomarker of dNLR and LDH can be used as a prognostic biomarker in patients with advanced PC treated with PD-1 inhibitors.

Serum lactate dehydrogenase activities as systems biomarkers for 48 types of human diseases

Most human diseases are systems diseases, and systems biomarkers are better fitted for diagnostic, prognostic, and treatment monitoring purposes. To search for systems biomarker candidates, lactate dehydrogenase (LDH), a housekeeping protein expressed in all living cells, was investigated. To this end, we analyzed the serum LDH activities from 172,933 patients with 48 clinically defined diseases and 9528 healthy individuals. Based on the median values, we found that 46 out of 48 diseases, leading by acute myocardial infarction, had significantly increased (p < 0.001), whereas gout and cerebral ischemia had significantly decreased (p < 0.001) serum LDH activities compared to the healthy control. Remarkably, hepatic encephalopathy and lung fibrosis had the highest AUCs (0.89, 0.80), sensitivities (0.73, 0.56), and specificities (0.90, 0.91) among 48 human diseases. Statistical analysis revealed that over-downregulation of serum LDH activities was associated with blood-related cancers and diseases. LDH activities were potential systems biomarker candidates (AUCs > 0.8) for hepatic encephalopathy and lung fibrosis.

Combining 18F-FDG PET/CT and Serum Lactate Dehydrogenase for Prognostic Evaluation of Small Cell Lung Cancer

Objective: To investigate the value of using ¹⁸F-FDG PET/CT in combination with serum lactate dehydrogenase (LDH) for prognostic evaluation of newly diagnosed small cell lung cancer (SCLC). Methods: We reviewed 118 patients with pathologically proven SCLC who underwent ¹⁸F-FDG PET/CT imaging evaluation in our hospital. Among these patients, 64 patients had extensive disease (ED) and 54 patients had limited disease (LD). The maximum standardized uptake value (SUV_max) of primary tumor was measured. A Cox proportional hazards model was used to evaluate age, sex, performance status, serum LDH, tumor stage and SUV_max on the prediction of overall survival (OS) and median survival time (MST) of patients. Subgroup analysis was performed based on the SUV_max in combination with serum LDH. Results: According to the Receiver Operating Characteristic (ROC) curve, the optimal cut-off value of SUV_max was 10.95. The AUC was 0.535 (95% CI: 0.407-0.663). The patients were divided into four groups according to the SUV_max (higher or lower than 10.95) and LDH (higher or lower than 245 U/L). The univariate and multivariate analyses showed that curative thoracic radiotherapy, Prophylactic Cranial Irradiation (PCI) and the combination of primary tumor SUV_max ≤ 10.95 and LDH ≤ 245 U/L were prognostic factors of OS in patients with all patients (p < 0.05). Smoking status, PCI, the combination of primary tumor SUV_max ≤ 10.95 and LDH ≤ 245 U/L were prognostic factors of OS in patients with LD (p < 0.05). N stage and PCI were significant predictors in both of univariate and multivariate analysis of OS for ED SCLC (p < 0.05). Among all patients, 27 had low SUV_max and normal LDH, and their MST was 36 months (95% CI: 12.98-59.02). Ninety-one patients had high SUV_max and/or high LDH, and their MST was 20 months (95% CI: 15.47-24.53). The difference between these two groups was significant (p = 0.045). In patients with LD, 16 patients had low SUV_max and normal LDH, and their MST was 72 months (95% CI: 26.00-118.0). Thirty-eight patients had high SUV_max and/or high LDH, and their MST was 27 months (95% CI: 20.80-33.21). The difference between these two groups was significant (p = 0.012). In patients with ED SCLC, 10 patients had low SUV_max and normal LDH, with an MST of 18 months (95% CI: 13.69-22.32. Fifty-four patients had high SUV_max and/or high LDH, and their MST was 12 months (95% CI: 10.61-13.39). The difference of MST between these two groups was not statistically significant (p = 0.686). Conclusion: ¹⁸F-FDG PET/CT in combination with serum LDH were prognostic factors of overall survival in patients with SCLC. The prognosis of patients with LD SCLC who had low SUV_max of primary tumor and normal LDH was better than those with high SUV_max and/or high LDH.

Association of the Pretreatment Lung Immune Prognostic Index with Survival Outcomes in Advanced Hepatocellular Carcinoma Patients Treated with PD-1 Inhibitors

Purpose

At present, there are no validated biomarkers that can predict whether patients with advanced hepatocellular carcinoma (aHCC) are likely to benefit from anti-PD-1 therapy. We aimed to determine whether lung immune prognostic index (LIPI) is associated with outcomes in patients with aHCC treated with PD-1 inhibitors.

Patients and Methods

Patients undergoing initial treatment with PD-1 inhibitors for aHCC at a single center from January 1, 2015 to August 31, 2019 were included. The patients were stratified according to pretreatment LIPI based on a derived neutrophils/(leukocytes minus neutrophils) ratio (dNLR) ≥ 3 and a lactate dehydrogenase (LDH) level ≥ the upper limit of normal (ULN). Kaplan–Meier analysis and the Log rank test were used to calculate and compare survival between good LIPI and intermediate/poor LIPI scores. The prognostic values of LIPI for survival and disease control rate were evaluated using Cox proportional hazard and logistic regression models, respectively.

Results

Of the 108 study patients, 53 (49%) had a good LIPI (dNLR < 3 and LDH normal) and 55 (51%) had intermediate/poor LIPI (dNLR ≥ 3 or/and LDH ≥ ULN). With a median follow-up of 12.4 months, intermediate/poor LIPI was independently associated with shorter overall survival (OS) (hazard ratio [HR] 4.00; 95% CI, 2.00–8.03) and progression-free survival (PFS) (HR 2.65; 95% CI, 1.61–4.37). The median OS for good and intermediate/poor LIPI was not reached and was 13.7 (95% CI, 8.2–19.1) months, respectively, and the median PFS was 10.9 (95% CI, 8.9–12.9) and 4.0 (95% CI, 2.2–5.8) months (both P < 0.001), respectively.

Conclusion

Pretreatment LIPI combined with a dNLR ≥ 3 and/or LDH ≥ ULN is associated with poor outcomes in patients with aHCC treated with PD-1 inhibitors. Further validation in large, prospective studies are warranted.

Development and validation of a novel nomogram to predict overall survival in gastric cancer with lymph node metastasis

Gastric cancer (GC) with lymph node metastasis (LNM) at diagnosis is associated with a unstable prognosis and indefinite survival times. The aim of the present study was to construct and validate a model for the Overall survival (OS) estimation for patients with LNM. The nomogram was constructed to predict the OS for LNM-positive GC using the primary group of 836 patients and validated using an independent cohort of 411 patients. Factors in the nomogram were identified by multivariate Cox hazard analysis. The predictive capability of nomogram was evaluated by calibration analysis and decision curve analysis. Multivariate analysis suggested that eight pre-treatment characteristics were used for developing the nomogram. In the primary cohort, the C-index for OS prediction was 0.788 (95% CI: 0.753-0.823), while in validation cohort, the C-index for OS prediction was 0.769 (95% CI: 0. 720-0.818). The calibration plot for the probability of OS and decision curve analyses showed an optimal agreement. Based on the nomogram, we could divided patients into three groups: low-risk group, middle-risk group and a high-risk group(p <0.001).Taken together, we have provided an easy-to-used and accurate tool for predicting OS, furthermore could be used for risk stratification of OS of LNM-positive GC patients.

Nomogram-based parameters to predict overall survival in a real-world advanced cancer population undergoing palliative care

Background

Although palliative care has been accepted throughout the cancer trajectory, accurate survival prediction for advanced cancer patients is still a challenge. The aim of this study is to identify pre-palliative care predictors and develop a prognostic nomogram for overall survival (OS) in mixed advanced cancer patients.

Methods

A total of 378 consecutive advanced cancer patients were retrospectively recruited from July 2013 to October 2015 in one palliative care unit in China. Twenty-three clinical and laboratory characters were collected for analysis. Prognostic factors were identified to construct a nomogram in a training cohort (n = 247) and validated in a testing cohort (n = 131) from the setting.

Results

The median survival time was 48.0 (95% CI: 38.1–57.9) days for the training cohort and 52.0 (95% CI: 34.6–69.3) days for the validation cohort. Among pre-palliative care factors, sex, age, tumor stage, Karnofsky performance status, neutrophil count, hemoglobin, lactate dehydrogenase, albumin, uric acid, and cystatin-C were identified as independent prognostic factors for OS. Based on the 10 factors, an easily obtained nomogram predicting 90-day probability of mortality was developed. The predictive nomogram had good discrimination and calibration, with a high C-index of 0.76 (95% CI: 0.73–0.80) in the development set. The strong discriminative ability was externally conformed in the validation cohort with a C-index of 0.75.

Conclusions

A validated prognostic nomogram has been developed to quantify the risk of mortality for advanced cancer patients undergoing palliative care. This tool may be useful in optimizing therapeutic approaches and preparing for clinical courses individually.

Electronic supplementary material

The online version of this article (10.1186/s12904-019-0432-7) contains supplementary material, which is available to authorized users.

A review of metabolism-associated biomarkers in lung cancer diagnosis and treatment

INTRODUCTION

Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection has proven essential to extend survival. Genomic and proteomic advances have provided impetus to the effort dedicated to detect and diagnose the disease at an earlier stage. Recently, the study of metabolites associated with tumor formation and progression has inaugurated the era of cancer metabolomics to aid in this effort.

OBJECTIVES

This review summarizes recent work regarding novel metabolites with the potential to serve as biomarkers for early lung tumor detection, evaluation of disease progression, and prediction of patient outcomes.

METHOD

We compare the metabolite profiling of cancer patients with that of healthy individuals, and the metabolites identified in tissue and biofluid samples and their usefulness as lung cancer biomarkers. We discuss metabolite alterations in tumor versus paired non-tumor lung tissues, as well as metabolite alterations in different stages of lung cancers and their usefulness as indicators of disease progression and overall survival. We evaluate metabolite dysregulation in different types of lung cancers, and those associated with lung cancer versus other lung diseases. We also examine metabolite differences between lung cancer patients and smokers/risk-factor individuals.

RESULT

Although an extensive list of metabolites has been evaluated to distinguish between these cases, refinement of methods is further required for adequate patient diagnosis.

CONCLUSION

We conclude that with technological advancement, metabolomics may be able to replace more invasive and costly diagnostic procedures while also providing the means to more effectively tailor treatment to patient-specific tumors.