Assessment of age as different variable types for determining survival in differentiated thyroid cancer

Identification of age- and immune-related gene signatures for clinical outcome prediction in lung adenocarcinoma

BACKGROUND

The understanding of the factors causing decreased overall survival (OS) in older patients compared to younger patients in lung adenocarcinoma (LUAD) remains.

METHODS

Gene expression profiles of LUAD were obtained from publicly available databases by Kaplan-Meier analysis was performed to determine whether age was associated with patient OS. The immune cell composition in the tumor microenvironment (TME) was evaluated using CIBERSORT. The fraction of stromal and immune cells in tumor samples were also using assessed using multiple tools including ESTIMATE, EPIC, and TIMER. Differentially expressed genes (DEGs) from the RNA-Seq data that were associated with age and immune cell composition were identified using the R package DEGseq. A 22-gene signature composed of DEGs associated with age and immune cell composition that predicted OS were constructed using Least Absolute Shrinkage and Selection Operator (LASSO).

RESULTS

In The Cancer Genome Atlas (TCGA)-LUAD dataset, we found that younger patients (≤70) had a significant better OS compared to older patients (>70). In addition, older patients had significantly higher expression of immune checkpoint proteins including inhibitory T cell receptors and their ligands. Moreover, analyses using multiple bioinformatics tools showed increased immune infiltration, including CD4+ T cells, in older patients compared to younger patients. We identified a panel of genes differentially expressed between patients >70 years compared to those ≤70 years, as well as between patients with high or low immune scores and selected 84 common genes to construct a prognostic gene signature. A risk score calculated based on 22 genes selected by LASSO predicted 1, 3, and 5-year OS, with an area under the curve (AUC) of 0.72, 0.72, 0.69, receptively, in TCGA-LUAD dataset and an independent validation dataset available from the European Genome-phenome Archive (EGA).

CONCLUSION

Our results demonstrate that age contributes to OS of LUAD patients atleast in part through its association with immune infiltration in the TME.

The association between the interval of radioiodine treatment and treatment response, and side effects in patients with lung metastases from differentiated thyroid cancer

Objective

Repeat radioiodine (RAI) treatment has been widely implemented for RAI-avid lung metastases and is clinically effective for lung metastatic differentiated thyroid cancer (DTC). We aim to investigate the association between the interval of RAI treatment and short-term response, and the side effects in patients with lung metastases from DTC and to identify predictors for non-effective response to the next RAI treatment.

Methods

A total of 282 course pairs from 91 patients were established and categorized into two groups by the interval of neighboring RAI treatment (<12 and ≥12 months), and the characteristics and treatment response between the two groups were compared. Multivariate logistic regression was used to identify predictors associated with treatment response. The side effects in the former course and the latter course were compared while taking into account the interval.

Results

No significant difference was found between the two groups in treatment response in the latter course (p > 0.05). In the multivariate analysis, age ≥ 55 years (OR = 7.29, 95% CI = 1.66-33.35, p = 0.008), follicular thyroid cancer (OR = 5.00, 95% CI = 1.23-22.18, p = 0.027), and a second RAI treatment as the former course (OR = 4.77, 95% CI = 1.42-18.61, p = 0.016) were significantly associated with a non-effective response. There was no significant difference in the side effects in the former and latter courses between the two groups (p > 0.05).

Conclusion

The interval of RAI treatment does not affect short-term response and side effects of DTC patients with RAI-avid lung metastases. It was feasible to defer repeat evaluation and treatment with an interval of at least 12 months to obtain an effective response and reduce the risk of side effects.

Development and validation of a survival prediction model and risk stratification for pancreatic neuroendocrine neoplasms

PURPOSE

We explored risk variables associated with cancer-specific survival (CSS) in patients with pancreatic neuroendocrine neoplasms (PNENs) and created a network dynamic nomogram model to predict patient survival time.

METHODS

A total of 7750 patients with PNENs were included in this analysis, including 134 with functional PNENs and 7616 with nonfunctional PNENs. Clinical feature and prognosis differences between functional and nonfunctional PNENs were compared. Independent prognostic factors affecting CSS were analyzed by univariate and multifactorial Cox regression. Nomogram and web-based prognosis prediction of PNENs were developed and validated by C indices, decision curve analysis, and calibration plots.

RESULTS

Patients with functional PNENs were younger at diagnosis than those with nonfunctional PNENs. Functional PNENs had better prognoses than nonfunctional PNENs (5-year survival rates: 78.55% and 71.10%, respectively). Univariate and multifactorial Cox regression analyses showed that tumor infiltration (T), nodal metastasis (N), metastasis (M), tumor site, differentiation grade, age, marital status, and surgical treatment were independent prognostic risk factors for CSS, which were included in the prognostic nomogram and web-based prognosis calculator. The calibration plots and decision curve analysis showed that the nomogram had excellent prediction and clinical practical ability. The C indices for CSS in the training and validation cohorts were 0.848 (95% CI 0.838-0.8578) and 0.823 (95% CI 0.807-0.839), respectively. We scored all patients according to the nomogram and divided patients into three different risk groups. The prognosis of the low-risk population was significantly better than those of the middle- and high-risk populations based on Kaplan-Meier survival curve.

CONCLUSION

We analyzed the clinical features of PNENs and developed a convenient and web dynamic nomogram to predict CSS.

Incomplete response to therapy in intermediate- and high-risk thyroid cancer

CONTEXT

The American Thyroid Association (ATA) risk stratification system predicts risk of recurrence of differentiated thyroid cancer (DTC). Although the majority of patients achieve an excellent response, patients with intermediate- or high-risk DTC are at a significant risk of developing incomplete responses. We undertook this work to understand the factors associated with development of biochemically or structurally incomplete response in these two risk subgroups of DTC.

PATIENTS AND METHODS

We retrospectively reviewed 287 consecutive patients with intermediate- (213 patients) or high-risk (74 patients) DTC. All patients underwent total thyroidectomy with (223 patients) or without (64 patients) lymph node dissection and 94% of them received at least one dose of I-131ablation/therapy. Univariate and multivariate analysis and Kaplan Meier analysis were used to compare patients who achieved an excellent response with those who continued to have biochemically or structurally incomplete responses.

RESULTS

In univariate and multivariate analyses, age (P 0.002, Odds ratio 4.8, 95% CI: 1.8-12.9), tumor size (P 0.027, Odds ratio 1.30, 95% CI: 1.03-1.64) and distant metastases (P &lt; 0.0001, Odds ratio 44.6, 95% CI: 10.7-184.5) were significantly associated with the risk of developing biochemically or structurally incomplete statuses. Patients ≥ 55 years, tumors &gt; 2.5 cm and presence of distant metastasis were associated with higher risk of incomplete response and death from DTC. However, when this analysis was performed on intermediate and high-risk groups separately, only age was consistently associated with risk of biochemically or structurally incomplete response in either and both groups.

CONCLUSION

Age is a strong predictor of biochemically and structurally incomplete responses in patients with intermediate and high-risk DTC.