Four-protein model for predicting prognostic risk of lung cancer

CK19 protein expression: the best cutoff value on the prognosis and the prognosis model of hepatocellular carcinoma

BACKGROUND AND OBJECTIVE

In clinical practice, CK19 can be an important predictor for the prognosis of HCC. Due to the high incidence and mortality rates of HCC, more effective and practical prognostic prediction models need to be developed urgently.

METHODS

A total of 1,168 HCC patients, who underwent radical surgery at the Guangxi Medical University Cancer Hospital, between January 2014 and July 2019, were recruited, and their clinicopathological data were collected. Among the clinicopathological data, the optimal cutoff value of CK19-positive HCC was determined by calculating the area under the curve (AUC) using survival analysis and time-dependent receiver operating characteristic (timeROC) curve analysis. The predictors were screened using univariate and multivariate COX regression and least absolute shrinkage and selection operator (LASSO) regression to construct nomogram prediction models, and their predictive potentials were assessed using calibration curves and AUC values.

RESULTS

The 0% positive rate of CK19 was considered the optimal cutoff value to predict the poor prognosis of CK19-positive HCC. The survival analysis of 335 CK19-positive HCC showed no significant statistical differences in the overall survival (OS) and disease-free survival (DFS) of CK19-positive HCC patients. A five-factor risk (CK19, CA125, Edmondson, BMI, and tumor number) scoring model and an OS nomograph model were constructed and established, and the OS nomograph model showed a good predictive performance and was subsequently verified.

CONCLUSION

A 0% expression level of CK19 protein may be an optimal threshold for predicting the prognosis of CK19-positive HCC. Based on this, CK19 marker a good nomogram model was constructed to predict HCC prognosis.

HSP90: A promising target for NSCLC treatments

The emergence of targeted therapies and immunotherapies has improved the overall survival of patients with nonsmall cell lung cancer (NSCLC), but the 5-year survival rate remains low. New drugs are needed to overcome this dilemma. Moreover, the significant correlation between various client proteins of heat-shock protein (HSP) 90 and tumor occurrence, progression, and drug resistance suggests that HSP90 is a potential therapeutic target for NSCLC. However, the outcomes of clinical trials for HSP90 inhibitors have been disappointing, indicating significant toxicity of these drugs and that further screening of the beneficiary population is required. NSCLC patients with oncogenic-driven gene mutations or those at advanced stages who are resistant to multi-line treatments may benefit from HSP90 inhibitors. Enhancing the therapeutic efficacy and reducing the toxicity of HSP90 inhibitors can be achieved via the optimization of their drug structure, using them in combination therapies with low-dose HSP90 inhibitors and other drugs, and via targeted administration to tumor lesions. Here, we provide a review of the recent research on the role of HSP90 in NSCLC and summarize relevant studies of HSP90 inhibitors in NSCLC.

Clinical application of common inflammatory and nutritional indicators before treatment in prognosis evaluation of non-small cell lung cancer: a retrospective real-world study

Objective

To evaluate the prognostic value of common clinical inflammatory and nutritional indicators before treatment in patients with non-small cell lung cancer in the real world.

Method

A total of 5,239 patients with pathologically confirmed non-small cell lung cancer from 2011 to 2018 in the Affiliated Cancer Hospital of Xinjiang Medical University were selected. Their inflammatory and nutritional indicators (RDW, PDW, NLR, LMR, NMR, PLR, SII, PNI, TP, ALB, CYRFA21-1, CEA, CA125, NSE, α1-globulin, α2-globulin, β1-globulin, β2-globulin, and γ-globulin) before treatment were collected. From the total number, 1,049 patients were randomly sampled (18 to 20% of patients each year) and used as the validation set; the remaining 4,190 patients were used as the training set. According to the eighth edition of the guidelines for the diagnosis, treatment, and stage risk stratification of lung cancer, the patients were divided into four groups: stage I/II operable, stage III operable, stage III inoperable, and stage IV. We used the X-tile software to intercept and classify the cut-off values of each index in the validation set. Univariate and multivariate Cox proportional-hazard regression were used to screen the independent risk factors affecting the prognosis of non-small cell lung cancer and establish a prognostic model for 1, 3, and 5 years. The validation set was used to verify its performance. Finally, the Kaplan-Meier curve was used to assess the survival rate, and the corresponding nomogram was established for clinical use.

Results

After screening, no effective indicators were found in the stage I/II operable group. RDW and CA125 were effective indicators for the stage III operable group (cut-off values were 14.1 and 9.21, respectively, compared with the low-value group; univariate HR was 2.145 and 1.612, and multivariate HR was 1.491 and 1.691, respectively). CYRFA21-1 and CA125 were effective prognostic indicators for the stage III inoperable group (cut-off values were 10.62 and 44.10, respectively, compared with the low-value group; univariate HR was 1.744 and 1.342, and multivariate HR was 1.284 and 1.304, respectively). CYRFA21-1, CA125, NLR, and α1-globulin were effective indicators of prognosis in stage IV (cut-off values were 3.07, 69.60, 4.08, and 5.30, respectively, compared with the low-value group; univariate HR was 1.713, 1.339, 1.388, and 1.539; and multivariate HR was 1.407, 1.119, 1.191, and 1.110, respectively). The model was constructed with the best validation power in stage IV patients (C-index = 0.733, 0.749, and 0.75 at 1, 3, and 5 years, respectively).

Conclusion

For patients with stage III and IV non-small cell lung cancer, some inflammatory markers, serum tumor markers, and nutritional indicators are independent prognostic factors. Combined with the general data of patients, the constructed prognostic evaluation model has the best efficacy in patients with stage IV and can be widely used in clinical practice.

Role of Serum CYFRA 21-1 in Diagnosis and Prognostic in Colorectal Liver Metastases

Purpose

In current studies, the role of serum Cytokeratin-19 fragments (CYFRA 21-1) in colorectal cancer (CRC) remains unclear. This study aimed to clarify the diagnostic and prognostic value of CYFRA 21-1 in CRC.

Patients and Methods

Data were collected for 196 stage I-III CRC patients and 50 colorectal liver metastases (CRLM) patients between January 2018 and December 2019. The serum CYFRA 21-1 levels were measured using the chemiluminescent particle immunoassay (CMIA) kit in all objects and common biomarkers such as CA19-9, CEA, HSP90α, and AFP were measured in all colorectal cancer patients. We investigated the association between CYFRA 21-1 level and clinicopathological features. In addition, we evaluated the ability of serum CRFRA21-1 to differentiate CRLM from CRC. To assess the potential prognostic value, we used Cox proportional hazard model for univariate or multivariate analyses.

Results

Serum CYFRA 21-1 was significantly elevated in CRLM patients compared to stage I-III CRC patients (5.85 ng/mL vs 2.29 ng/mL, p < 0.001). For all CRC patients cohort, stage I-III CRC patients cohort and CRLM patients cohort, the optimal cutoff levels of CYFRA 21-1 for overall survival (OS) were 3.47 ng/mL, 2.14 ng/mL and 7.63 ng/mL, respectively, and the optimal cutoff levels for progression-free survival (PFS) were 3.47 ng/mL, 2.56 ng/mL and 7.63 ng/mL, respectively. For CRLM patients, Kaplan-Meier analysis showed that patients with high CYFRA 21-1 level had poor OS. Multivariate analysis indicated that the CYFRA 21-1 level was an independent prognostic factor for PFS in stage I-III patients. And CYFRA 21-1 levels and age were independent prognostic factors for OS and PFS in CRLM patients.

Conclusion

CYFRA 21-1 can better differentiate CRLM patients from the whole CRC patients and has unique prognostic value for CRLM patients.