Clinical impact of cerebral infarction in patients with non-small cell lung cancer

Development of an algorithm for identifying paraneoplastic ischemic stroke in association with lung, pancreatic, and colorectal cancer

Background

Paraneoplastic ischemic stroke has a poor prognosis. We have recently reported an algorithm based on the number of ischemic territories, C-reactive protein (CRP), lactate dehydrogenase (LDH), and granulocytosis to predict the underlying active cancer in a case-control setting. However, co-occurrence of cancer and stroke might also be merely incidental.

Objective

To detect cancer-associated ischemic stroke in a large, unselected cohort of consecutive stroke patients by detailed analysis of ischemic stroke associated with specific cancer subtypes and comparison to patients with bacterial endocarditis.

Methods

Retrospective single-center cohort study of consecutive 1612 ischemic strokes with magnetic resonance imaging, CRP, LDH, and relative granulocytosis data was performed, including identification of active cancers, history of now inactive cancers, and the diagnosis of endocarditis. The previously developed algorithm to detect paraneoplastic cancer was applied. Tumor types associated with paraneoplastic stroke were used to optimize the diagnostic algorithm.

Results

Ischemic strokes associated with active cancer, but also endocarditis, were associated with more ischemic territories as well as higher CRP and LDH levels. Our previous algorithm identified active cancer-associated strokes with a specificity of 83% and sensitivity of 52%. Ischemic strokes associated with lung, pancreatic, and colorectal (LPC) cancers but not with breast and prostate cancers showed more frequent and prominent characteristics of paraneoplastic stroke. A multiple logistic regression model optimized to identify LPC cancers detected active cancer with a sensitivity of 77.8% and specificity of 81.4%. The positive predictive value (PPV) for all active cancers was 13.1%.

Conclusion

Standard clinical examinations can be employed to identify suspect paraneoplastic stroke with an adequate sensitivity, specificity, and PPV when it is considered that the association of ischemic stroke with breast and prostate cancers in the stroke-prone elderly population might be largely incidental.

Short‐term outcomes in patients with lung cancer‐associated acute ischemic stroke

Background

To investigate the independent risk factors of poor short‐term outcomes in patients with lung cancer‐associated acute ischemic stroke (LCAIS) and use them to develop an index of prognosis LCAIS (pLCAIS) which could help clinicians identify patients at high risk for poor short‐term outcomes.

Methods

We retrospectively enrolled patients with lung cancer‐associated acute ischemic stroke and employed the 90D modified Rankin cale (mRS) to divide them into two groups: good outcomes (score 0–2) and poor outcomes (score 3–6). Propensity score matching (PSM) was used to remove confounding factors, and multivariable logistic regression analysis was used to analyze the independent risk factors of pLCAIS. The receiver operating characteristic (ROC) and area under the ROC curve (AUC) developed a multiple model combining the independent risk factors of pLCAIS.

Results

A total of 172 patients were included: 67 (38.9%) with good outcomes and 105 (61.1%) with poor outcomes. After using PSM, there were 33 cases in each group. The results showed that patients with poor short‐term outcomes were significantly higher in D‐dimer (OR = 1.001, 95% CI: 1.000–1.002, p = 0.048), CRP (OR = 1.078, 95% CI: 1.008–1.153, p = 0.028), and neutrophil count (OR = 14.673, 95% CI: 1.802–19.500, p = 0.012). The ROC curve, used to assess the diagnostic ability of binary classifiers, showed that the product of these three independent risk factors showed high sensitivity and specificity.

Conclusion

In this study, we have identified three independent risk factors associated with poor short‐term outcomes in pLCAIS: higher NC, CRP, and D‐dimer levels. These findings may be helpful for clinicians in identifying poor short‐term outcomes patients.

Upregulation of CCNB2 and Its Perspective Mechanisms in Cerebral Ischemic Stroke and All Subtypes of Lung Cancer: A Comprehensive Study

Cyclin B2 (CCNB2) belongs to type B cell cycle family protein, which is located on chromosome 15q22, and it binds to cyclin-dependent kinases (CDKs) to regulate their activities. In this study, 103 high-throughput datasets related to all subtypes of lung cancer (LC) and cerebral ischemic stroke (CIS) with the data of CCNB2 expression were collected. The analysis of standard mean deviation (SMD) and summary receiver operating characteristic (SROC) reflecting expression status demonstrated significant up-regulation of CCNB2 in LC and CIS (Lung adenocarcinoma: SMD = 1.40, 95%CI [0.98–1.83], SROC = 0.92, 95%CI [0.89–0.94]. Lung squamous cell carcinoma: SMD = 2.56, 95%CI [1.64–3.48]. SROC = 0.97, 95%CI [0.95–0.98]. Lung small cell carcinoma: SMD = 3.01, 95%CI [2.01–4.01]. SROC = 0.98, 95%CI [0.97–0.99]. CIS: SMD = 0.29, 95%CI [0.05–0.53], SROC = 0.68, 95%CI [0.63–0.71]). Simultaneously, protein-protein interaction (PPI) analysis indicated that CCNB2 is the hub molecule of crossed high-expressed genes in CIS and LC. Through Multiscale embedded gene co-expression network analysis (MEGENA), a gene module of CIS including 76 genes was obtained and function enrichment analysis of the CCNB2 module genes implied that CCNB2 may participate in the processes in the formation of CIS and tissue damage caused by CIS, such as “cell cycle,” “protein kinase activity,” and “glycosphingolipid biosynthesis.” Afterward, via single-cell RNA-seq analysis, CCNB2 was found up-regulated on GABAergic neurons in brain organoids as well as T cells expressing proliferative molecules in LUAD. Concurrently, the expression of CCNB2 distributed similarly to TOP2A as a module marker of cell proliferation in cell cluster. These findings can help in the field of the pathogenesis of LC-related CIS and neuron repair after CIS damage.