Adverse effects of being underweight on young female breast cancer patients with lymph node metastases

Chen, Bin; Lai, Jianguo; Guo, Liping; Dai, De-Chang; Chen, Rong; Wei, Guodong; Liao, Ning

doi:10.7150/jca.38567

Cited by 14 publications

(17 citation statements)

References 33 publications

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“…Another study found that chemotherapy was frequently incomplete in UW patients [41], but our data suggested that this did not cause poorer prognosis because there were only a few patients who were unable to complete chemotherapy in our study. Some investigators cited the more aggressive breast cancer characteristics among younger patients, who comprised a large proportion of UW subjects, as a reason for poor prognosis [37,43,46,47]; however, this was also not supported by our data. Others posited that the immune system is dysfunctional in UW individuals owing to chronic malnutrition and micronutrient de ciency [43,51,52].…”

Section: Discussioncontrasting

confidence: 93%

“…including one pooled analysis, demonstrated poor survival outcomes not only in OB patients with breast cancer but also in UW patients [11,[37][38][39][43][44][45][46][47][48][49][50]. However, there were difference in each subtype; some studies found that UW patients with HRBC had poorer prognoses [47][48][49] and that those with HER2BC or TNBC did not [47,49].…”

Section: Discussionmentioning

confidence: 99%

“…Depending on the study, UW patients were found to be younger [37,43], have smaller tumors [37,42,43], rarely have lymph node metastases [37,42], and have lower histologic grades [37]; one study showed them to have more frequent HER2 positivity [44], another found them to have more frequent hormone receptor positivity [37], and two others found them to be more frequently hormone receptor-negative [42,43]. Regarding prognosis, a number of studies, including one pooled analysis, demonstrated poor survival outcomes not only in OB patients with breast cancer but also in UW patients [11,[37][38][39][43][44][45][46][47][48][49][50]. However, there were difference in each subtype; some studies found that UW patients with HRBC had poorer prognoses [47][48][49] and that those with HER2BC or TNBC did not [47,49].…”

Section: Discussionmentioning

confidence: 99%

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Clinical verification of body mass index and tumor immune response in patients with breast cancer receiving preoperative chemotherapy

Takada

Kashiwagi

Asano

et al. 2021

Preprint

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Purpose: The body mass index (BMI) is commonly used as a simple indicator of obesity; patients with early-stage breast cancer who are obese (OB) per BMI measurements have been shown to have high postoperative recurrence and low survival rates. On the other hand, it has been shown that lymphocytes present in the vicinity of malignant growths that are involved in the tumors’ immune responses influence the efficacy chemotherapy. Therefore, we hypothesized that OB patients with breast cancer have a lower density of tumor-infiltrating lymphocytes (TILs), which may influence the therapeutic effect of preoperative chemotherapy (POC). In this study, we measured pretreatment BMI and TILs in patients with breast cancer who underwent POC, examined the correlations between these two factors, and retrospectively analyzed their therapeutic outcomes and prognoses.Methods: The participants in this study were 421 patients with breast cancer who underwent surgical treatment after POC between February 2007 and January 2019. The patient’s height and weight were measured before POC to calculate the BMI (weight [kg] divided by the square of the height [m2]). According to the World Health Organization categorization, patients who weighed under 18.5 kg/m2 were classified as underweight (UW), those ≥18.5 kg/m2 and >25 kg/m2 were considered normal weight (NW), those ≥25 kg/m2 and <30 kg/m2 were overweight (OW), and those ≥30 kg/m2 were OB. The TILs were those lymphocytes that infiltrated the tumor stroma according to the definition of the International TILs Working Group 2014.Results: The median BMI was 21.9 kg/m2 (range, 14.3–38.5 kg/m2); most patients (244; 64.5%) were NW. Among all 378 patients with breast cancer, the TIL density was significantly lower in OB than in NW and OW patients (vs. NW: p=0.001; vs. OW: p=0.003). Furthermore, when examining patients with each breast cancer type individually, the OS of those with TNBC who had low BMIs was significantly poorer than that of their high-BMI counterparts (log rank p=0.031).Conclusions: Our data did not support the hypothesis that obesity affects the tumor immune microenvironment; however, we showed that being UW does affect the tumor immune microenvironment.

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Section: Discussioncontrasting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Clinical verification of body mass index and tumor immune response in patients with breast cancer receiving preoperative chemotherapy

Takada

Kashiwagi

Asano

et al. 2021

Preprint

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“…anorexia athletica) or low muscle mass, muscular atrophy [ 42 ], cardiovascular abnormalities, valvular dysfunction, compromised immunity [ 43 ]; cancer —particularly poor outcomes of some cancers, potentially decreased tolerability/effectiveness of cancer treatment e.g. due to lower haemoglobin and albumin resulting from abnormal nutritional status, cachexia, impaired anti-tumour immunity [ 44 ], loss of muscle fat mass, sarcopenia [ 45 ], increased risk of several cancer types and metastatic disease [ 6 , 46 , 47 ]; impaired healing and increased post-surgical complications —abnormal nutritional status, insufficient energy supply, shifted metabolic pathways and microbiome alterations [ 4 , 24 , 48 ], potentially low preoperative haemoglobin [ 49 , 50 ]; reproductive dysfunction —disruption of hypothalamic-pituitary–gonadal axis leading to hypothalamic anovulation [ 51 ], ovulatory dysfunction [ 52 ], negative effects on IVF parameters [ 53 – 55 ]; compromised immunity —abnormal nutritional status, lymphopenia [ 56 ]; respiratory infections including COVID-19 —malnutrition [ 57 ], coexisting chronic conditions [ 58 ], immuno-suppression as a result of malnutrition [ 59 ]; eating disorders (anorexia nervosa) —negative effects on overall and reproductive health [ 60 ]; neurological disorders such as young stroke [ 12 ] and abnormal pain sensitivity / perception [ 4 , 7 ]; abnormal sleep patterns [ 7 , 11 , 15 ] and depression [ 61 ]; primary vascular dysregulation —abnormal nutrition, low energy supply, Flammer syndrome, high Endothelin-1 level in blood plasma, increased stress sensitivity, amongst others [ 4 , 9 , 15 , 17 , 62 ]; Sicca syndrome with severe complications [ 11 , 13 , 15 ]. …”

Section: Systemic Effects and Health Risks Associated With Low Body Weightmentioning

confidence: 99%

Caution, “normal” BMI: health risks associated with potentially masked individual underweight—EPMA Position Paper 2021

et al. 2021

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An increasing interest in a healthy lifestyle raises questions about optimal body weight. Evidently, it should be clearly discriminated between the standardised “normal” body weight and individually optimal weight. To this end, the basic principle of personalised medicine “one size does not fit all” has to be applied. Contextually, “normal” but e.g. borderline body mass index might be optimal for one person but apparently suboptimal for another one strongly depending on the individual genetic predisposition, geographic origin, cultural and nutritional habits and relevant lifestyle parameters—all included into comprehensive individual patient profile. Even if only slightly deviant, both overweight and underweight are acknowledged risk factors for a shifted metabolism which, if being not optimised, may strongly contribute to the development and progression of severe pathologies. Development of innovative screening programmes is essential to promote population health by application of health risks assessment, individualised patient profiling and multi-parametric analysis, further used for cost-effective targeted prevention and treatments tailored to the person. The following healthcare areas are considered to be potentially strongly benefiting from the above proposed measures: suboptimal health conditions, sports medicine, stress overload and associated complications, planned pregnancies, periodontal health and dentistry, sleep medicine, eye health and disorders, inflammatory disorders, healing and pain management, metabolic disorders, cardiovascular disease, cancers, psychiatric and neurologic disorders, stroke of known and unknown aetiology, improved individual and population outcomes under pandemic conditions such as COVID-19. In a long-term way, a significantly improved healthcare economy is one of benefits of the proposed paradigm shift from reactive to Predictive, Preventive and Personalised Medicine (PPPM/3PM). A tight collaboration between all stakeholders including scientific community, healthcare givers, patient organisations, policy-makers and educators is essential for the smooth implementation of 3PM concepts in daily practice.

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“…Observational studies revealed the association between overweight/obesity and several measures of reduced prognosis in patients with breast cancer, and some instances of lower survival in women who are underweight or who experience unexplained weight loss after diagnosis. Our previous study demonstrated that being underweight was an independent prognostic factor for poor overall survival in young breast cancer patients with axillary lymph node metastasis or stage III-IV ( 5 ). A recent study found that overweight/obese patients with breast cancer treated with a docetaxel-based adjuvant chemotherapy regimen presented worse prognosis and an increased risk of developing distant metastases than lean patients with breast cancer treated with the same chemotherapy regimen ( 6 ).…”

Section: Introductionmentioning

confidence: 99%

Association of Body Mass Index With Somatic Mutations in Breast Cancer

Chen

Guo

et al. 2021

Front. Oncol.

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BackgroundThe relationship between body mass index (BMI) and the prognosis or treatment response in patients with breast cancer has been demonstrated in previous studies, but the somatic mutation profiles in breast cancer patients with different BMIs have not been explored.MethodsIn the present study, the somatic mutation profiles in 421 female breast cancer patients who were stratified into three subgroups based on BMI (normal weight, overweight/obese, and underweight) were investigated. Capture-based targeted sequencing was performed using a panel comprising 520 cancer-related genes.ResultsA total of 3547 mutations were detected in 390 genes. In breast cancer patients with different BMI statuses, the tumors exhibited high mutation frequency and burden. TP53 was the most common gene in the three groups, followed by PIK3CA, ERBB2, and CDK12. Meanwhile, the mutation hotspots in TP53 and PIK3CA were the same in the three BMI groups. More JAK1 mutations were identified in underweight patients than those in normal patients. Except for JAK1, differentially mutated genes in postmenopausal patients were completely different from those in premenopausal patients. The distribution of mutation types was significantly different among BMI groups in the postmenopausal group. Underweight patients in the postmenopausal group harbored more TP53 mutations, more amplifications, and more mutations in genes involved in the WNT signaling pathway.ConclusionsOur next-generation sequencing (NGS)-based gene panel analysis revealed the gene expression profiles of breast cancer patients with different BMI statuses. Although genes with high mutation frequency and burden were found in different BMI groups, some subtle differences could not be ignored. JAK1 mutations might play a vital role in the progression of breast cancer in underweight patients, and this needs further analysis. Postmenopausal underweight patients with breast cancer have more aggressive characteristics, such as TP53 mutations, more amplifications, and more mutations in genes involved in the WNT signaling pathway. This study provides new evidence for understanding the characteristics of breast cancer patients with different BMIs.

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Adverse effects of being underweight on young female breast cancer patients with lymph node metastases

Cited by 14 publications

References 33 publications

Clinical verification of body mass index and tumor immune response in patients with breast cancer receiving preoperative chemotherapy

Clinical verification of body mass index and tumor immune response in patients with breast cancer receiving preoperative chemotherapy

Caution, “normal” BMI: health risks associated with potentially masked individual underweight—EPMA Position Paper 2021

Association of Body Mass Index With Somatic Mutations in Breast Cancer

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