Progressive, multi‐organ, and multi‐layered nature of cancer cachexia

Abstract

Cancer cachexia is a complex, multifaceted condition that negatively impacts the health, treatment efficacy, and economic status of cancer patients. The management of cancer cachexia is an essential clinical need. Cancer cachexia is currently defined mainly according to the severity of weight loss and sarcopenia (i.e., macrosymptoms). However, such macrosymptoms may be insufficient to give clinicians clues on how to manage this condition as these symptoms appear at the late stage of cancer. We need to understand earlier events during the progression of cancer cachexia so as not to miss a clinical opportunity to control this complex syndrome. Recent research indicates that cancer‐induced changes in the host are much wider than previously recognized, including disruption of liver function and the immune system. Furthermore, such changes are observed before the occurrence of visible distant metastases (i.e., in early, localized cancers). In light of these findings, we propose to expand the definition of cancer cachexia to include all cancer‐induced changes to host physiology, including changes caused by early, localized cancers. This new definition of cancer cachexia can provide a new perspective on this topic, which can stimulate the research and development of novel cancer cachexia therapies.

We propose that host abnormalities begin even before the defined precachexia and that such earlier phases are potentially a better therapeutic window.

1. INTRODUCTION

Cancer cachexia is currently viewed as a multifactorial syndrome characterized by unintentional loss of appetite, weight, and skeletal muscle, all of which are outward, macrosymptoms. In detail, patients with more than 5% weight loss over the past 6 months, or a body mass index of less than 20 kg/m² and ongoing weight loss of more than 2%, or sarcopenia and ongoing weight loss of more than 2% are diagnosed as cachexia ¹ (Figure 1). It is also suggested that cancer cachexia cannot be completely reversed by nutritional support. ¹ , ² Patients with cancer cachexia often accompany metabolic disorders, systemic inflammation, and active catabolism, but these are currently not used to define cancer cachexia in clinics. Indeed, we do not have specific molecular markers to define cancer cachexia. Cancer cachexia eventually reduces the quality of life and treatment efficacy and increases medical costs (i.e., financial toxicity) in patients. ³ , ⁴ , ⁵ Despite the well‐known negative impacts of cancer cachexia on patients, assessment and management of cancer cachexia is limited and in need of further development. ¹ , ²

FIGURE 1.

The current definition of cancer cachexia. Cachexia is defined as a multistep disorder having precachexia, cachexia, and refractory cachexia. The criteria used depend mostly on macrophenotypes, and no specific biomarkers for evaluating cancer cachexia are available.

The current definition of cancer cachexia neither provides a comprehensive picture of cancer‐induced host pathophysiology nor offers specific biomarkers and therapeutic targets. The emergence of visible symptoms indicates that patients' homeostasis is already strongly dampened, passing the point of no return (Figure 2). Indeed, a previous study defined cancer cachexia as a multiphase disorder consisting of precachexia, cachexia, and refractory cachexia and pointed out the importance of beginning treatments in precachexia. ¹ Yet, these categories are still defined mostly by macrosymptoms, and we are even unsure if precachexia is still manageable. Clinicians may thus face significant challenges in managing and treating cancer cachexia due to the limited guidance from the current definition.

FIGURE 2.

Cancer cachexia is a progressive disorder. This figure depicts a schematic view of host pathophysiology in cancer cachexia. We propose that host abnormalities begin even before the defined precachexia and that such earlier phases are potentially a better therapeutic window.

We want to point out a need to expand the concept of cancer cachexia to include the whole disruption of host physiology in earlier disease stages even before the currently defined precachexia because such an earlier phase may be the optimal time to initiate treatments (Figure 2). This idea is important for clinicians not to overlook a critical opportunity to prevent or treat cancer cachexia. We insist that the current definition, which focuses too much on weight loss and muscle wasting, needs to be revised in the future. Due to the prevailing conception of cancer cachexia, many clinicians and researchers may regard cancer cachexia as an irreversible state in which no treatment is effective and only palliation of symptoms can be done. As a result, some clinicians and researchers may view the treatment of cancer cachexia as a fruitless endeavor, causing delays in the progress of research and development of treatment in cancer cachexia. We are motivated to solve these issues to advance cancer cachexia research.

2. A COMPREHENSIVE PICTURE OF CANCER CACHEXIA

2.1. Host pathophysiology in cancers

To emphasize our new perspective, we use the term “cancer cachexia” as “host pathophysiology in cancers.” Host pathophysiology in cancers includes all possible changes caused by cancers at all stages including when it is still local. Our focus is not limited to organs that have historically been the focus of cancer cachexia research, such as the muscle, but encompasses all host organs and cells (i.e., adding a multi‐organ view; Figure 3A).

FIGURE 3.

The need for multi‐organ and multi‐omics views in cancer cachexia. (A) Host pathophysiology in cancers includes all possible changes caused by cancers at all host organs not limited to muscle and adipose tissues that have been the focus of cancer cachexia research. (B) Multi‐omics analyses provide a comprehensive view of the host pathophysiology at multiple levels. This will aid in the elucidation of the mechanisms of cancer cachexia and the development of novel therapies for cancer cachexia.

Cancer‐induced disruption occurs in organs far away from the site of cancers, possibly before the onset of detectable metastasis. The effects of cancers on the host most likely change during the progression of cancers from local to metastatic disease. Hence, it is critically important to view cancer cachexia from a temporal perspective (Figure 2). It is also crucial to use multi‐omics analyses to provide a comprehensive view of the disruption of host physiology at multiple levels (e.g., upregulation/downregulation of genes, spatial changes of gene expression, disruption of metabolism, organ inflammation, etc.; Figure 3B). Adding such multi‐layer views is essential because we still do not know the entire picture of host pathophysiology in cancer cachexia. Such a comprehensive, multilevel view can help us to better understand the mechanisms of cancer cachexia.

Adding these three perspectives in cancer cachexia (progressive, multi‐organ, and multi‐omics), we summarize recent studies in the following sections. Although there are a series of seminal important cancer cachexia studies in Drosophila, ⁶ , ⁷ , ⁸ , ⁹ , ¹⁰ , ¹¹ we do not go into detail about such fly studies and focus on vertebrate studies due to space limitations.

2.2. Muscle and adipose tissues

Atrophy of skeletal muscle is a typical phenotype of cancer cachexia, and some host factors are known to be involved in this process. ¹² , ¹³ , ¹⁴ , ¹⁵ Bodine et al. ¹² found that genetic deletion of muscle RING finger 1 (MuRF1) and muscle atrophy F‐box (MAFbx) prevents the loss of muscle in mouse cancer models. Myostatin and activin are members of the transforming growth factor β (TGFβ) family and are involved in skeletal muscle atrophy by binding to the activin type II receptor B (ActR IIB). ¹³ Zhou et al. ¹⁴ reported that the pharmacological blockade of the ActR IIB pathway prevents the atrophy of skeletal muscle and cardiac muscle and prolongs survival in mouse cancer models. Shum et al. ¹⁵ performed proteomic profiling of muscle in a mouse cancer model and detected the downregulation of proteins involved in pathways of energy metabolism in the muscle.

Loss of adipose tissues is also a common phenotype in cancer cachexia. ¹⁶ , ¹⁷ , ¹⁸ , ¹⁹ , ²⁰ Cancer‐associated loss of adipose tissues is attributed to the increase in lipolysis, which is mediated by adipose triglyceride lipase (ATGL) and hormone‐sensitive lipase (HSL). ¹⁶ Das et al. ¹⁶ reported that genetic deletion of these enzymes prevents cancer‐induced lipolysis, adipose loss, and skeletal muscle loss in mouse cancer models. Switching from white adipose to brown fat, a phenomenon termed “browning” of white adipose tissues, contributes to the progression of cancer cachexia. ¹⁷ , ¹⁸ The interleukin‐6 (IL‐6) signaling pathway plays a critical role in cancer‐induced browning. ¹⁷ Parathyroid‐related peptide (PTHrP) from cancers and the host PTH receptor (PTHr) are crucial for this phenomenon. ¹⁸ , ¹⁹ Dahlman et al. ²⁰ demonstrated that the loss of adipose tissues is accompanied by alterations in gene expression associated with energy metabolism.

2.3. Liver

The liver had not been a major focus in cancer cachexia research. Nonetheless, recent studies including ours have shed light on the importance of liver metabolism to understand cancer cachexia.

2.3.1. Cholesterol metabolism and inflammation

We previously found that intestinal tumors (dysplasia) induce liver inflammation and disruption of liver metabolism in juvenile zebrafish, and identified a cholesterol metabolism factor cyp7a1 to mediate this pathophysiology. ²¹ Juvenile zebrafish harboring intestinal tumors driven by kras ^G12D , a well‐known oncogene, exhibited liver inflammation and decreased bile alcohol synthesis despite the lack of visible metastasis to the liver. ²¹ Interestingly, juvenile zebrafish with intestinal tumor also exhibited stunted growth (i.e., reduced body length) compared with their tumor‐free counterparts, indicating that intestinal tumors may induce growth defects. ²¹ It was also observed that cyp7a1 was downregulated in tumor‐bearing zebrafish. ²¹ Overexpression of cyp7a1 in tumor‐bearing zebrafish resulted in restoration of bile alcohol synthesis and amelioration of tumor‐induced liver inflammation. ²¹ These results indicated cyp7a1 as a host factor that mediates tumor‐induced liver inflammation and tumor‐induced decrease in bile alcohol synthesis. Despite being very basic, this study raised the possibility that even local cancers can cause systemic phenotypes in organisms, suggesting the need to look at systemic phenotypes even before detectable metastasis.

2.3.2. Circadian disruption

Several studies indicate that solid cancers can distantly cause circadian disruption in the liver. The circadian rhythm is a molecular mechanism that confers an approximately 24‐h rhythm in biological phenomena. A study by Hojo et al. ²² showed that the daily expression patterns of several circadian core clock genes, such as Clock, were altered in the livers of mice harboring 4T1 breast cancer. Similarly, the expression patterns of several downstream genes (i.e., genes regulated by the core clock genes), such as E2f8, were also disrupted in the livers of mice having 4T1 breast cancer. ²² Masri et al. ²³ reported that genetically induced lung cancers rewire the circadian rhythm in the liver as well, indicating the generality of cancer‐induced circadian disruption in host organs. Verlande et al. ²⁴ further showed, using the same lung cancer model, that loss of REV‐ERBα circadian transcription factor promotes cancer‐induced abnormalities in glucose metabolism. Their findings suggested that elevated hepatic glucose production via loss of REV‐ERBα could be beneficial for cancer metabolism. ²⁴ Interestingly, the livers of 4T1‐bearing mice exhibited increased inflammation, oxidative stress, and tetraploidy compared with the livers of cancer‐free mice. ²² These results highlight the disruption in host liver physiology at multiple levels (transcriptome, metabolome, organ, polyploidy) and emphasize the need to obtain an unbiased understanding of the whole pathophysiology in host organs.

2.3.3. Nicotinamide metabolism

A study by Mizuno et al. ²⁵ investigated the role of Nnmt in cancer‐induced disruption of liver metabolism using mouse models. At the transcriptome level, expression of Nnmt in the liver is increased after transplantation of various different solid cancers into mice. ²⁵ At the metabolome level, the livers of 4T1 breast cancer‐bearing mice accumulated citrulline, aspartate, arginine, and ornithine compared with cancer‐free mice. ²⁵ These four metabolites are members of the urea cycle, which is crucial for converting toxic ammonia to relatively nontoxic urea. Urea cycle dysregulation by breast and lung cancers was rescued by Nnmt knockout, suggesting that Nnmt is a mediator of this disruption. ²⁵ A recent comprehensive multi‐omics study using different cancer models also captured changes in the NNMT pathway, indicating the general role of NNMT in host pathophysiology in cancer cachexia. ²⁶

Beltra et al. ²⁷ investigated nicotinamide adenine dinucleotide (NAD⁺) metabolism in the liver and muscle using three different mouse cancer models: Colon26‐bearing mice treated with Folfox chemotherapy, KPC cancer‐bearing mice (a representative model of pancreatic ductal carcinoma), and Villin‐Cre/Msh2^loxP/loxP (VCM) mice. They found that Colon26‐bearing mice and VCM mice exhibit depletion of NAD⁺ in the liver. ²⁷ Rescuing NAD⁺ depletion by niacin supplementation ameliorated cancer‐induced loss of body weight and muscle mass. ²⁷ They also found that cancer patients show the downregulation of muscle Nrk2 (an NAD⁺ biosynthetic enzyme) even in weight‐stable cancer patients. ²⁷ Their findings highlighted the inability of the current assessment of cancer cachexia according to weight loss to detect muscle abnormalities such as Nrk2 downregulation. ²⁷ These studies introduced in this section shed light on the importance of nicotinamide‐related metabolism in cancer cachexia.

2.3.4. Disruption in liver zonation

We recently found that distant breast cancers can alter the spatial patterns of gene expression in the liver. ²⁸ Spatially‐regulated gene expression in the liver is critical for liver functioning and is called liver zonation. We used spatial transcriptomics and single‐cell RNA‐seq to investigate the spatial variation of gene expression in the livers of 4T1‐bearing mice. ²⁸ We observed that, in control mice, expression of genes associated with the “xenobiotic catabolic process” was highly active in hepatocytes harboring high expression of Cyp2e1, a marker for liver zonation. ²⁸ However, this localized expression was not observed in the livers of 4T1‐bearing mice, suggesting that the presence of 4T1 breast cancer disrupted zonated expression of genes involved in the “xenobiotic catabolic process. ²⁸ ” In addition, we discovered cancer‐induced switching of the biological functions of Albumin (Alb)‐high hepatocytes in the liver from metabolism to acute phase response. ²⁸ In 4T1‐bearing mice, genes associated with the “acute phase response” were upregulated in a zonated manner, having higher expression levels in Alb‐high zones. ²⁸ These results suggest the utility of combining gene expression data with spatial data in order to obtain a comprehensive view of how distant cancers change the physiology of the liver.

Serum amyloid alpha 1 and 2 (SAA1‐2) are representative acute phase response proteins. ²⁹ To determine whether or not Saa1 and Saa2 are mediators of cancer‐induced liver inflammation, Saa1‐2‐knockout mice were generated, and 4T1 breast cancer cells were transplanted to the Saa1‐2‐knockout mice. ²⁹ This study demonstrated that there was no significant difference in liver inflammation between the cancer‐bearing Saa1‐2‐knockout mice and the cancer‐bearing wild‐type mice. ²⁹ These results suggest that Saa1‐2 are not necessary for cancer‐induced liver inflammation in the 4T1 breast cancer mouse model. ²⁹ This study is a good example that correlations in gene expression do not always accompany functional significance.

2.3.5. Ketone metabolism

Using the Colon26 model and the genetically engineered model of pancreatic ductal adenocarcinoma (PDA), Flint et al. ³⁰ found that cancer‐induced IL‐6 suppresses hepatic ketogenesis in precachectic mice. During caloric deficiency, suppressed hepatic ketogenesis elevates glucocorticoid levels. ³⁰ Elevation of glucocorticoid induced by metabolic stress suppresses intratumoral T cell immunity in Colon26‐bearing mice. ³⁰ They also demonstrated that stress‐induced glucocorticoids cause failure of anticancer immunotherapy in a mouse PDA model. ³⁰ These results indicated that metabolic dysregulation in cancer hosts can impair host immunity, ³⁰ which is related to the next section about the immune system.

2.4. Immune system

We recently expanded our cancer cachexia research to human cancer patients, finding local and systemic immunosuppression in breast cancer patients. Combining transcriptome, spatial transcriptome, and imaging mass cytometry against paired nonmetastatic and metastatic lymph nodes in the same breast cancer patients, Maeshima et al. ³¹ recently revealed that breast cancer cells reduce the number of CD169⁺ lymph node sinus macrophages in metastatic lymph nodes. CD169⁺ macrophages play a role in an early step of anticancer immunity as they phagocytose cancer‐derived antigens and present them to CD8⁺ T cells. ³² Hence, the elimination of CD169⁺ macrophages in the lymph nodes can be regarded as a sign of local immunosuppression. Our data also indicated that the elimination of CD169⁺ macrophages precedes abnormalities in other immune cells and systemic inflammation. ³¹ These results implicate CD169⁺ macrophages as an early target of immunosuppression by breast cancers in lymph nodes. ³¹

In a study by Nakamura et al., ³³ we performed transcriptome analysis in peripheral blood mononuclear cells and plasma metabolome analysis within the same breast cancer patients with visceral metastasis to reveal host pathophysiology in metastatic breast cancer patients. For the purpose of stratifying patients using quantitative values rather than regarding them as the same group, we focused on albumin levels. ³³ Our transcriptome data indicated that low albumin levels are correlated with an increase in neutrophils and a decrease in CD8⁺ T cells. ³³ We also found a decrease in immunoregulatory metabolites, such as arginine in plasma correlating with albumin levels. ³³ We verified these results by using the 4T1 breast cancer model. ³³ From the results of these two studies, we hypothesize that breast cancers suppress the immune system both locally and systemically (Figure 4).

FIGURE 4.

Local and systemic immunosuppression in breast cancer patients. (A) Breast cancer cells reduce the number of CD169⁺ lymph node sinus macrophages in metastatic lymph nodes. The elimination of CD169⁺ macrophages in the lymph nodes can be considered as a sign of local immunosuppression. (B) In metastatic breast cancer patients, low albumin levels are correlated with an increase in neutrophils and a decrease in CD8⁺ T cells in PBMC. Similarly, an immunoregulatory metabolite, such as arginine, decreases in the plasma of metastatic breast cancer patients correlating with albumin levels. These results indicate that low albumin levels are correlated with systemic immunosuppression in metastatic breast cancer patients. PBMC, peripheral blood mononuclear cells.

Kawaguchi and colleagues demonstrated systemic alteration of the immune system in breast cancer patients. ³⁴ , ³⁵ They captured altered expression in immunity‐related genes in peripheral blood mononuclear cells during the progression of breast cancer. ³⁴ Blood cytokine profiles were also different between breast cancer patients and healthy volunteers. ³⁵

Allen et al. ³⁶ reported alterations in the immune system during cancer progression in mouse models. They demonstrated that cancers progressively alter the immune environment as they develop, highlighting the importance of the temporal dynamics of cancer‐induced immunosuppression. ³⁶ Specifically, they found that neutrophils were progressively increased, and CD4⁺ T cells and CD8⁺ T cells were progressively decreased, in the spleen and blood overgrowth of 4 T1 breast cancers, ³⁶ which is in line with our observations. Furthermore, they also revealed that this systemic alteration of immune cell frequencies can be rescued by complete resection of cancers, and local recurrence and lung metastasis resulted in a partial relapse of the immune environment to a state similar to the pre‐resection state. ³⁶ These results indicate that cancer‐induced immunosuppression in mouse cancer models is reversible, at least if the cancer is not yet terminal. ³⁶ Based on these results, we suggest that there exists a window of time in which it is possible to reverse cancer‐induced immunosuppression in breast cancer patients. Previous research has indicated that the intact immune macroenvironment is favorable for anticancer immunotherapy. ³⁷ , ³⁸ Therefore, if such a reversible phase exists in human cancer patients, then it would be of great importance to identify this phase and utilize it to improve the outcomes of immunotherapy.

3. POTENTIAL INTERVENTION FOR CANCER CACHEXIA

Despite the widespread occurrence of cachexia in cancer patients, very few treatment options are currently available. Nevertheless, important discoveries have been made in recent years which may lay the foundations for new treatment methods.

3.1. Preclinical models

There are several studies reporting potential interventions for cancer cachexia using animal models. As described earlier, the blockage of ActR IIB and niacin supplementation are emerging candidates to manage cancer cachexia. ¹⁴ , ²⁷ Talbert et al. ³⁹ reported a MEK inhibitor MEK162 to have anticachectic effects in a colon cancer mouse model Colon26. Colon‐26 mice treated with MEK162 for 16 days experienced significantly mitigated levels of weight loss compared with control Colon‐26 mice. ³⁹ MEK162‐treated mice also had larger muscle masses compared with control mice. Wyart et al. ⁴⁰ showed that iron supplementation is effective in ameliorating muscle atrophy in cancer cachexia. From a different perspective, the gut microbiota is also a target for cancer cachexia therapy. Bindels et al. ⁴¹ revealed disruption of the gut microbiome in a mouse model of leukemia (BaF) and colon cancer (Colon26). The results from these preclinical models are important to find therapeutic targets for treating cancer cachexia in the future.

3.2. Clinical data

3.2.1. Exercise

Previous research has also indicated that exercise may be an effective treatment for cancer cachexia. Galvão et al. ⁴² performed a clinical trial which investigated the effects of aerobic and resistance exercise on prostate cancer patients without bone metastases undergoing androgen suppression therapy (AST). The group of patients who performed exercise had significantly greater lean mass and significantly better muscle strength and walking time compared with the control group. ⁴² Another clinical trial was performed by Galvão et al. ⁴³ to investigate the effects of multimodal exercise (aerobic, resistance, and flexibility) on prostate cancer patients with bone metastases. They found that the group which performed multimodal exercise had significantly improved self‐reported physical functioning and improved lower body muscle strength compared with the control group, although there were no significant differences for lean mass, fat mass, and fatigue. ⁴³

3.2.2. Anamorelin

Most importantly, anamorelin is an emerging agent for cancer cachexia therapy. Anamorelin is a selective ghrelin receptor agonist that promotes the secretion of growth hormone and thus appetite. ⁴⁴ In 2020, anamorelin was approved in Japan for treating cancer cachexia specifically in non‐small cell lung cancer (NSCLC), gastric cancer, pancreatic cancer, and colorectal cancer based on the results from the following two Japanese prospective studies. ⁴⁴ In a randomized, double‐blind, placebo‐controlled trial of 174 patients with stage III/IV NSCLC, anamorelin‐treated patients showed an increase in lean body mass and an improvement in appetite. ⁴⁵ There was no significant improvement in hand grip strength and 6‐min walk test in the anamorelin arm. ⁴⁵ The other study was a nonrandomized study of 50 patients with advanced gastrointestinal cancer and showed an improvement in lean body mass. ⁴⁶ Anamorelin was not approved for use in the United States and Europe due to the results from two international phase III trials (ROMANA 1 and ROMANA 2) and an extended study (ROMANA III) conducted on patients with stage III/IV NSCLC. ⁴⁴ , ⁴⁷ , ⁴⁸ These trials showed improvements in muscle mass and appetite but failed to prove an effect on hand grip strength. ⁴⁷ , ⁴⁸ For approval in the United States and Europe, the improvement of muscle strength and physical function needs to be proven. ⁴⁴

3.2.3. Growth differentiation factor 15

Growth differentiation factor 15 (GDF15) is also an attractive target for cancer cachexia therapy. ⁴⁹ GDF15 contributes to anorexia and weight loss by binding to glial cell‐derived neurotrophic factor family receptor α‐like (GFRAL) in the feeding center of the brainstem. ⁵⁰ Borner et al. ⁵¹ found that the GDF15‐GFRAL signaling pathway causes emesis and nausea prior to the onset of anorexia. Circulating GDF15 was associated with weight loss and poor survival in cancer patients and increased by platinum‐based chemotherapy. ⁵² , ⁵³ Antibody‐mediated inhibition targeting GDF15‐GFRAL signaling reversed cancer‐induced weight loss in a mouse model. ⁵⁴ Blockade of GDF15 attenuated platinum‐based chemotherapy‐induced anorexia and weight loss and promoted survival in a mouse cancer model. ⁵³ These results indicate the applicability of the inhibition of GDF15‐GFRAL signaling in the treatment of anorexia.

These emerging therapeutic strategies are promising. Yet, too much focus on macrophenotypes may overlook other therapeutic opportunities, as already discussed. In this respect, it is crucial to use molecular, “invisible” phenotypes to evaluate the efficacy of developing therapies in an unbiased manner (Figure 3).

In this review, we presented our proposed new perspective on cancer cachexia. We consider cancer cachexia to include all cancer‐induced changes to host physiology. To support our view, we summarized several recent research papers which indicate that cancer‐induced changes to host physiology are broader than previously thought. These research papers indicate that cancers can cause disruptions in areas that were previously not considered part of cancer cachexia (i.e., classical cachexia), such as liver metabolism and immune system function. Expanding this concept will broaden the scope of research and development of treatment in cancer cachexia by introducing a perspective consisting of three main parts: multi‐omics analysis, multi‐organ dysfunction, and the progression of cancer cachexia during cancer development. We hope that this perspective on cancer cachexia will lead to new therapies that target host factors, thereby buffering cancer‐induced host pathophysiology and improving the health and quality of life of cancer patients. Incurable cancers will no longer be a problem if we can efficiently control and manage cancer cachexia and if we do not die from cancers.

AUTHOR CONTRIBUTIONS

Yuki Nakamura: Conceptualization; visualization; writing – original draft; writing – review and editing. Don Pietro Saldajeno: Conceptualization; visualization; writing – original draft; writing – review and editing. Kosuke Kawaguchi: Conceptualization; funding acquisition; writing – review and editing. Shinpei Kawaoka: Conceptualization; funding acquisition; supervision; visualization; writing – original draft; writing – review and editing.

FUNDING INFORMATION

This work was supported by JSPS KAKENHI (20H03451 to S.K.; 19K16770 and 21K15530 to K.K.), JST FOREST (20351876 to S.K), Caravel, Co., Ltd (to S.K), and the Japan Foundation for Applied Enzymology (to S.K.).

CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest regarding this work.

ETHICS STATEMENT

Approval of the research protocol by an Institutional Review Board: N/A.

Informed Consent: N/A.

Registry and the Registration No. of the study/trial: N/A.

Animal Studies: N/A.

Nakamura Y, Saldajeno DP, Kawaguchi K, Kawaoka S. Progressive, multi‐organ, and multi‐layered nature of cancer cachexia. Cancer Sci. 2024;115:715‐722. doi: 10.1111/cas.16078