The sensitivity and specificity of serum glycan-based biomarkers for cancer detection

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The sensitivity and specificity of serum glycan-based biomarkers for cancer detection Yang Tanga,b, Yidi Cuia,b, Shufeng Zhangc, Lijuan Zhanga,b,* a

Systems Biology & Medicine Center for Complex Diseases, Affiliated Hospital of Qingdao University, Qingdao, China b School of Medicine and Pharmacy, Ocean University of China, Qingdao, China c College of Chemistry, Tianjin Normal University, Tianjin, China *Corresponding author: e-mail address: [email protected]

Contents 1. Introduction 2. Clinically used cancer biomarkers developed based on hybridoma technology 2.1 CA125 2.2 CA153 2.3 CA549 2.4 CA27.29 2.5 CA199 2.6 CA195 2.7 CA50 2.8 CA724 2.9 CA242 2.10 Squamous cell cancer antigen 3. Other clinically used cancer biomarkers 3.1 α-Fetoprotein 3.2 Carcinoembryonic antigen of iron 3.3 Carcinoembryonic antigen 3.4 Pancreatic oncofetal antigen 3.5 Prostate-specific antigen 3.6 Human chorionic gonadotropin 3.7 Span-1 3.8 OVX1 4. Conclusions and future perspectives Acknowledgments Conflicts of interest References

Progress in Molecular Biology and Translational Science ISSN 1877-1173 https://doi.org/10.1016/bs.pmbts.2019.01.010

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2019 Elsevier Inc. All rights reserved.

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Abstract Most of clinically used serum biomarkers for cancer detection were established in early 1980s when the Nobel Prize in physiology or medicine was awarded for the “discovery of the principle for the production of monoclonal antibodies.” Using this “Nobel” technology, various monoclonal antibodies were obtained when different types of cancer cells were injected into mice and the ligands on the cancer cell surface were characterized. Both aberrant glycan structures and aberrant glycan-associated glycoproteins were revealed as a common feature of cancer cell surfaces through the specific interactions with the monoclonal antibodies. These results indicate that the biosynthesis of the environment-sensitive glycan structures goes awry in cancer cells, which is beyond genetic mutations. Later on, the glycan-related biomarkers were detected in the sera of cancer patients and then developed into serum biomarkers, such as CA125, CA153, CA195, CA199, CA242, CA27.29, CA50, and CA724, which are still in clinical use as of today. During the past 30 years, even with the advancement of different OMICS technologies not limited to genomics, epigenomics, proteomics, glycomics, lipidomics, and metabolomics, very few serum biomarkers have been introduced into clinical practice. The reason is that most of the newly discovered cancer biomarkers are inferior in terms of sensitivity and specificity to these biomarkers. We will summarize the reported sensitivity and specificity of currently used cancer biomarkers, especially the glycanrelated biomarkers, in the forms of tables and radar plots and discuss the pros and cons of currently used cancer biomarkers.

1. Introduction Cancer biomarkers are biological molecules that suggest the presence of cancer in a patient. They are either produced by the cancer cells or by noncancer cells in response to cancer.1 Cancer biomarkers identified from serum are the mostly desirable form of the biomarkers that can be used for personalized daily care in screening, diagnosis, establishing prognosis, monitoring treatment, and detecting relapse. The basic molecular building blocks of human life includes the well-known 20 amino acids that are used to make proteins and the 8 nucleosides that compose DNA and RNA along with 9 monosaccharides that make different kinds of glycans and 8 kinds of lipids.2 Unlike the RNAs and proteins, the glycans and the lipids are not directly encoded by DNA but regulate human physiology and pathology ranging from signal transduction to microbial infections.3 Therefore, valid serum/plasma-based lung cancer biomarkers could be protein/peptides as well as DNA, RNA, glycans, lipids, and metabolites present in blood circulation.4,5 A good biomarker has to have excellent sensitivity and specificity.6 Sensitivity refers to the biomarker’s ability to correctly detect patients who do

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have the condition whereas specificity relates to biomarker’s ability to correctly reject healthy individuals without a condition. For example, if 100 patients known to have a disease were tested for the specific biomarker, and 50 test positive, then the test has 50% sensitivity. If 100 with no disease are tested and 90 return a negative result, then the test has 90% specificity. Other characteristics of a good biomarker, such as high positive or negative predictive values are dependent not only on sensitivity and specificity, but also on the disease prevalence. Most of currently used clinical cancer biomarkers, such as CA125, CA153, CA195, CA199, CA242, CA27.29, CA50, and CA724, were discovered using the monoclonal antibodies generated by the hybridoma technology established in 1970s.7 These biomarkers are either special glycan structures or glycoproteins with special glycan structures with moderate sensitivity and specificity. However, despite the emergence of highly powerful OMICS technologies not limited to genomics, epigenomics, proteomics, glycomics, lipidomics, and metabolomics, very few serum biomarkers have been introduced into clinical practice in the last 30 years.8 The reason is that most of the newly discovered cancer biomarkers are inferior in terms of sensitivity and specificity to the clinically used biomarkers.9 Glycans are the most information dense biomolecules that are made in each cell and distributed throughout all organs and tissues in the human body.10,11 Glycans are involved in many physiological and pathological conditions, such as intracellular transport, cell adhesion, cell–cell interactions, host–pathogen interactions, cell differentiation, migration, blood coagulation, tumor invasion and metastasis, cell trafficking, and signaling.12–24 Glycans are not directly encoded in a genetic template. As secondary gene products, the information in glycans reflects the impact of both internal and external factors, such as diseases, lifestyle, and social factors, on a person’s health and disease, which provides a rational explanation why currently used cancer biomarkers are mostly glycan structure dependent. In this chapter, we will focus on the serum levels of currently used cancer biomarker and will summarize their reported sensitivity and specificity in the forms of tables and radar plots and discuss the pros and cons of cancer biomarkers.25–27

2. Clinically used cancer biomarkers developed based on hybridoma technology The era for cancer biomarker discovery started when the hybridoma technology became available in 1970s.7 The CA125, CA153, CA549,

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CA27.29, CA199, CA195, CA50, CA724, CA242, and SCCA were subsequently established as serum cancer biomarkers and used daily in clinic. The molecular nature and clinical applications of these biomarkers are summarized in Table 1. The reported sensitivity and specificity for each of these biomarkers are summarized in Table 2.

2.1 CA125 CA125 is a heavily glycosylated mucin protein and was first identified as an ovarian cancer antigen in 1981. The monoclonal antibody used to detect CA125 is OC125. The increased serum CA125 levels detected by the monoclonal antibodies were subsequently developed into a diagnostic and prognostic biomarker for ovarian cancer. However, later studies showed that CA125 could be the biomarkers for different types of cancers, such as for pancreatic and endometrial cancers, as well as for benign diseases, such as endometriosis, fibroid uterus, acute salpingitis, hepatopathy, chest peritoneal, and pericardial infection. The reference value for normal serum CA125 level is less than 35 U/mL. The sensitivities of CA125 for pancreatic and ovarian cancer detection are 45%–57% and 65%,28,29 respectively. The specificities of CA125 for pancreatic and ovarian cancer detection are 76%–78%30–32 and 97%,28,29 respectively. Table 1 Clinical used biomarkers developed based on hybridoma technology. Biomarker Molecular type Clinical use Cancer type

CA125

Mucin

Monitoring

Ovarian and endometrial cancers

CA153

Mucin

Monitoring

Breast and ovarian cancers

CA549

Mucin

Monitoring

Breast and ovarian cancers

CA27.29

Mucin

Monitoring

Breast cancer

CA199

Glycan

Monitoring

Pancreatic, gastrointestinal, and liver cancers

CA195

Glycan

Monitoring

Gastrointestinal and ovarian cancers

CA50

Glycan

Monitoring

Pancreatic, gastrointestinal, and colon cancers

CA724

Glycan

Monitoring

Ovarian, breast, gastrointestinal, and colon cancers

CA242

Glycan

Monitoring

Colorectal and pancreatic cancers

SCCA

Serine protease Monitoring inhibitor

Squamous cell carcinomas

Table 2 The sensitivity and specificity of clinically used biomarkers developed based on hybridoma technology. Monoclonal antibodies Reference Name used value Sensitivity Specificity References

OC125

<35 U/mL

Pancreatic cancer: 45%–57%, Ovarian cancer: 65%

Pancreatic cancer: 76%–78%, Ovarian cancer: 97%

28–32

CA153

DF3, 115D8

<28 U/mL

Breast cancer: 61.5%–70%

Breast cancer: 81%–90%

33–35

CA549

BC4E549, BC4n154

0.1–11 U/mL Breast cancer: 70%

Breast cancer: 61.5%–70%

36

<25 U/mL

Breast cancer: 84%

33

CA27.29 B27, B29

Breast cancer: 39%

CA199

116NS19-9 <37 U/mL

Pancreatic cancer: 70%–90%, Pancreatic cancer: 68%–91%， 28,37–71 Colorectal cancer: 18%–65%， Colorectal cancer: >90%， Ovarian cancer: 24% Ovarian cancer: 88.2%

CA195

116NS19-5 <20 U/mL

Pancreatic cancer: 76%–85%

CA50

Colo-50

CA724

B27.3.cc49 <6.7 μg/L

CA242

C242

<17 U/mL

Pancreatic cancer: 65%–82%， Pancreatic cancer: 65%–95%， 40,45–47,51,54,60,65–67,70,74–79 Colorectal cancer: 33%–55% Colorectal cancer: 35%–96%

SCCA

Antiserum

<1.5 μg/L

Lung, skin, head, and neck cancers

Pancreatic cancer: 73%–85%

30,72,73

0.1–20 U/mL Pancreatic cancer: 65%–96%， Pancreatic cancer: 34%–90%， 39,43,46–48,51,52,60,70,74–77 Colorectal cancer: 24%–67% Colorectal cancer: 57%–99% Colorectal cancer: 25%–43%

Colorectal cancer: 95%–98%

Squamous cell carcinomas

61,63,65,67,70

N/A

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CA125

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2.2 CA153 CA153 was originally discovered as a breast cell antigen recognized by two monoclonal antibodies DF3 and 115D8 simultaneously. Subsequent studies showed that DF3 recognizes the core protein of mucin1 whereas 115D8 recognizes part of the glycan chains on MUC1. MUC1 is a highly glycosylated transmembrane protein expressed on the mucosal surfaces of epithelial cells in lung, breast, stomach, gallbladder, lymph node, colon, rectum, and pancreas. The increased serum levels of CA153 have been established as a biomarker for both breast and ovarian cancer diagnosis since 1980s. The reference value for normal serum CA153 level is <28 U/mL. The sensitivity of CA153 for breast cancer detection is 61.5%–70%.33–35 The specificity of CA153 for breast cancer detection is 81%–90%.33–35

2.3 CA549 CA549 was also established as a breast cell antigen recognized by two monoclonal antibodies BC4E549 and BC4n154 simultaneously. The antigen is also a mucin-type glycoprotein with high molecular weight. Clinically, CA549 is used for breast and ovarian cancer detection. The normal reference ranges for serum CA549 level is 0.1–11 U/mL. The sensitivity of CA549 for breast cancer detection is 70%.36 The sensitivity of CA549 for breast cancer detection is 84%.

2.4 CA27.29 CA27.29 is a mucin-type glycoprotein with high molecular weight. Clinically, CA27.29 is used as the biomarker for breast cancer. The two monoclonal antibodies used for detecting CA27.29 are B27 and B29. The normal reference value for serum CA27.29 level is <25 U/mL. For breast cancer detection, the sensitivity is 84%33 while the specificity is 84%.33

2.5 CA199 The CA199 epitope was identified as a glycan containing sialylated Lewisa structural motif. CA199 could be used as biomarkers for both cancers and benign diseases, such as pancreatic cancer, gastrointestinal cancer, liver cancers, pancreatitis, and jaundice. The monoclonal antibody used to detect CA199 is 116NS19-9. The normal reference value of CA199 is <37 U/mL. The sensitivities are 70%–90%37–57 for pancreatic cancer, 18%–65%46,58–70 for colorectal cancer, and 24%28,71 for ovarian cancer. The specificities are 68%–91%37–47,58 for pancreatic cancer 90%46,58–70 for colorectal cancer, and 88.2%28,71 for ovarian cancer.

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2.6 CA195 The epitope of CA195 is identified as a sialyl Lewisa-containing glycan structure. It is used for pancreatic, gastrointestinal, and ovarian cancer detection. The monoclonal antibody used to detect CA195 is 116NS19-5. The normal reference value for serum CA195 level is <20 U/mL. For pancreatic cancer detection, the sensitivity is 76%–85%30,72,73 and the specificity is 73%–85%.30,72,73

2.7 CA50 The CA50 epitope recognized by the monoclonal antibody is glycan structures including sialyl-lacto-N-tetraose and sialyl Lewisa antigen. CA50 has the same antigenic determinant as CA199, but CA50 has a unique sialyl Lewisa structure that lacks a fucosyl residue. CA50 is biomarker for many diseases including cancer and benign diseases. Cancers include pancreatic, gastrointestinal, and colon cancers, while benign diseases include pancreatitis, colitis, and pneumonia. The monoclonal antibody used to detect serum CA50 level is colo-50. The normal reference value is 0.1–20 U/mL. The sensitivities are 65%– 96%39,43,46–48,51,52,60,74,75 and 24%–67%46,60,70,76,77 for pancreatic cancer and colorectal cancer, respectively. The specificities are 34%– 90%39,43,46–48,51,52,60,74,75 and 57%–99%46,60,70,76,77 for pancreatic cancer and colorectal cancer, respectively.

2.8 CA724 Early studies showed that CA724 is a tumor-associated glycoprotein (TAG72) with a molecular weight of more than 1000 kDa. Subsequently, its epitope is identified as sialyl Tn glycan or sialyl-α (2-6)-N-acetylgalactosamine. CA724 is used as the biomarker for ovarian, breast, gastrointestinal, and colon cancer detections. The monoclonal antibody used to detect CA724 is B27.3.cc49. The normal reference value for serum CA724 is <6.7 μg/L. For colorectal cancer detection, the sensitivity is 25%–43%61,63,65,67,70 whereas the specificity is 95%–98%.61,63,65,67,70

2.9 CA242 CA242 is a novel sialic acid-containing glycan structure that is covalently linked to glycoproteins or glycolipids in serum. It is used as the biomarker of colorectal and pancreatic cancer. The common monoclonal antibody used to detect CA242 is C242. The normal reference value for serum CA242 is <17 U/mL.

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The sensitivities for pancreatic and colorectal cancer detection are 65%– 82%40,45–47,51,54,60,74,75 and 33%–55%,46,60,64,65,67,70,76–79 respectively. The specificities for pancreatic and colorectal cancer detection are 65%– 95%40,45–47,51,54,60,74,75 and 35%–96%,46,60,64,65,67,70,76–79 respectively.

2.10 Squamous cell cancer antigen Squamous cell cancer antigen (SCCA) was purified by using antiserum generated by hybridoma technique that specifically binds to squamous cell carcinomas of human uterine cervix in the 1977.80 Molecular biology studies demonstrate that SCCA belongs to the super family of serine protease inhibitors (SERPINs) and functions as suicide substrates for cellular proteases. SCCA comprises two highly homologous isoforms, SCCA1 and SCCA2, which are encoded by two genes, SERPINB3 and SERPINB4, located on the long arm of chromosome 18 (18q21.3), respectively. Clinically, SCCA is used as the biomarker of lung, skin, head, and neck cancers. The normal reference value for serum SCCA is <1.5 μg/L.

3. Other clinically used cancer biomarkers The molecular nature and clinical applications of the biomarkers developed by biochemical or other approaches are summarized in Table 3. The reported sensitivity and specificity for each of these biomarkers are summarized in Table 4.

3.1 α-Fetoprotein α-Fetoprotein (AFP) was first found in human fetal serum by Bergstrandh and Czar in 1956. AFP is a glycoprotein and belongs to the gene family of serum albumins. The molecular biology studies showed that AFP consists of 591 amino acids and is modified with one N-glycan chain at the 232nd Asn residue. The serum AFP levels were found to be elevated in the sera of liver cancer patients in 1964 and were subsequently developed and used as a liver cancer biomarker. AFP are biomarkers for both cancers and benign diseases. Cancers include liver and germ cell cancers (nonspermatogonium cancer). Benign diseases include viral hepatitis, cirrhosis, fetuses with spina bifida, anencephalus, fetal asphyxia, and threatened abortion. The normal reference value for serum AFP level in the adult is <25 μg/L. The sensitivity is 41%–65%81–86 for liver cancer and 22% for breast cancer.33 The specificity is 80%–94%81–86 for liver cancer and 88% for breast cancer.33

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Table 3 Other clinically used cancer biomarkers. Molecular Name type Clinical use

AFP (α-fetoprotein)

Glycoprotein Screening and monitoring

Cancer type

Liver cancer, nonspermatogonium cancer

Carcinoembryonic Glycoprotein Monitoring antigen of iron

Liver cancer

CEA (carcino Glycoprotein Monitoring embryonic antigen)

Colon, rectum, pancreatic, lung, and breast cancers

POA (pancreatic oncofetal antigen)

Glycoprotein Monitoring

Pancreatic cancer

PSA (prostatespecific antigen)

Serine protease

Screening and monitoring

Prostatic cancer

HCG (human chorionic gonadotropin)

Hormone

Staging

Embryonic chorion, testicular cancers (nonspermatogonium cancer)

Span-1

Mucin

Monitoring

Pancreatic cancer

OVX1

Mucin

Diagnosis

Early endometrial cancer

3.2 Carcinoembryonic antigen of iron The carcinoembryonic antigen (CEA) of iron is a glycoprotein with a molecular weight of 600 kDa. Clinically, CEA of iron is used as a biomarker for liver cancer. The normal reference value for males is 30–400 μg/L and for females is 13–150 μg/L.

3.3 Carcinoembryonic antigen CEA was first identified as colon cancer antigen in 1965. CEA belongs to the immunoglobulin superfamily of cell adhesion molecules. Its core protein has a molecular weight of 79 kDa and actual CEA has a molecular weight of 70–100 kDa with covalently linked glycans mainly consisting N-acetylglucosamine, mannose, galactose, fucose, and sialic acid. Clinically, CEA is used as the biomarker of Colon, rectum, pancreas, lung, and breast cancers. The clinically normal reference value of CEA is less than 5 μg/L but in smokers, the value is less than 10 μg/L.

Table 4 The sensitivity and specificity of other clinically used cancer biomarkers. Name Reference value Sensitivity Specificity

References

AFP

<25 μg/L

Liver cancer: 41%–65%, breast carcinoma: 22%

CEA

<5 μg/L Smoker: <10 μg/L

Pancreatic cancer: 40%–92%, Pancreatic cancer: 59%– colorectal cancer: 43%–69%, 90%，colorectal cancer: breast cancer: 22%–56.9% 55%–98%，breast cancer: 80%–93.6%

33,34,37–47,58–68,70, 74,76,78,87–90

POA (pancreatic oncofetal antigen)

<18.6 mg/L

Pancreatic cancer: 68%–81% Pancreatic cancer: 88%–96%

30,91,92

PSA (prostatespecific antigen)

0–4.0 μg/L

Prostatic cancer: 63%–93%

Prostatic cancer: 75%–95%

93–98

HCG (human chorionic gonadotropin)

Male: <5 mU/mL, Unpregnant women: <75 mU/mL

Gallbladder cancer: 60%, pancreatic cancer: 46%, gastric cancer: 40%, liver cancer: 20%, colorectal cancer: 15%

N/A

99–103

OVX1

Pancreatic cancer: 81%–89% Pancreatic cancer: 67%–85% 2.23  2.48 U/mL Ovarian cancer: 40.1%

Ovarian cancer: 82.7%

40,42,43,48,58 28,71

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Span-1

Liver cancer: 80%–94%, breast 33,81–86 carcinoma: 88%

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The sensitivity of pancreatic cancer is 40%–92%,37–47,74 colorectal cancer is 43%–69%,46,58–68,70,76,78,87–90 and breast cancer is 56.9%，22%.33,34 The specificity of pancreatic cancer is 59%–90%,37–47,74 colorectal cancer is 55%–98%,46,58–68,70,76,78,87–90 and breast cancer is 93.6%, 80%.33,34

3.4 Pancreatic oncofetal antigen Pancreatic oncofetal antigen (POA) is a glycoprotein with a molecular weight of 40 kDa. POA was extracted from fetal pancreas by Banwo in 1974 and formally named by the International Cancer Biology and Medicine in 1979. Clinically, POA is used as the biomarker of pancreatic cancer. The clinically normal reference value of POA is less than 18.6 mg/L. The sensitivity of pancreatic cancer is 68%–81%,30,91,92 while the specificity is 88%– 96%.30,91,92

3.5 Prostate-specific antigen Prostate-specific antigen (PSA) was first found by Hara in 1971. It was synthesized from prostate epithelial cells and secreted into the semen. It is the main element of the seminal plasma. PSA is a glycoprotein also known as kallikrein 3 (KLK3) with a molecular weight of 34 kDa, mainly produced by the prostate. PSA is a serine protease. PSA is used only as the biomarker of prostatic cancer. The normal reference value of PSA is less than 4.0 μg/L. The sensitivity of prostatic cancer is 63%–93%.93–98 The specificity of prostatic cancer is 75%–95%.93–98

3.6 Human chorionic gonadotropin Human chorionic gonadotropin (HCG) is secreted by placental trophoblastic cells. It is a glycoprotein with a molecular weight of 45 kDa and can be detected in the blood of normal pregnant women. HCG could be biomarkers for both cancers and benign diseases, which include embryonic chorion and testicular cancers (nonspermatogonium cancer), endometriosis, and ovarian cyst. The normal reference value for serum HCG is <5 mU/mL in males and less than 75 mU/mL in female women. The sensitivities are 60% for gallbladder cancer, 46% for pancreatic cancer, 40% for gastric cancer, 20% for liver cancer, and 15% for colorectal cancer.99–103

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3.7 Span-1 Span-1 is a mucin-like glycoprotein with a high molecular weight. It is used as the biomarker of pancreatic cancer. The sensitivity is 81%– 89%37,42,43,47,48 whereas the specificity is 67%–85%37,42,43,47,48

3.8 OVX1 OVX1 is a mucin-like glycoprotein with high molecular weight. It is used as the biomarker for ovarian cancer. The normal reference value for OVX1 is 2.23  2.48 U/mL. The sensitivity is 40.1%28,71 while the specificity is 82.7%.28,71

4. Conclusions and future perspectives To pursue cancer biomarker with high sensitivity and high specificity, the cancer research field has produced over 20 serum biomarkers for cancer monitoring. By surveying the literature, we summarized the reported sensitivities and specificities of these biomarkers in Tables 2 and 4. Since most of the biomarkers have wide ranges of reported sensitivities and specificities for the same type of cancer, to visualize the results, the radar plots for ovarian, breast, colorectal, and pancreatic cancers of several selected biomarkers are shown in Fig. 1. The areas with solid color represent the ranges between the maximum and minimum values of reported sensitivities or specificities. The common scenario was that the higher sensitivity and specificity were associated with early reports of discovery and lower sensitivity and specificity were associated with later confirming studies. If high sensitivity and high specificity are indices for ideal cancer markers, only a few biomarkers satisfy the two conditions simultaneously. Thus, the limitations for current biomarkers are (1) the low sensitivity for most of the biomarkers produces false negative results for cancer patients; (2) the low specificity for most of biomarkers produces false positive results for healthy individuals; (3) near all serum biomarker levels are elevated in benign diseases; (4) only extremely elevated serum biomarker levels in a small percentages of patients produce 100% specificity for cancer diagnosis; (5) most of serum biomarker levels are not elevated in early stage of cancer development; and (6) only certain biomarkers with their elevated serum levels correlate with cancer recurrence and developmental stage. All these characteristics make these biomarkers usable and essential for modern medicine. Unfortunately, none of these biomarkers are ideal for cancer screening or early diagnosis.

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Fig. 1 The radar plots of sensitivities and specificities of different biomarkers in ovarian, breast, colorectal, and pancreatic cancers.

The question is what makes it so hard to develop reliable cancer biomarker for patient care. Cancer used to be considered as rapid growth and spread of cancer cells in human body due to genetic mutations in cancer cells. However, the inherited genetic defects from a person’s parents only contribute approximately 5%–10% causes of cancers.104,105 The studies led by Bissell et al. indicate that it is the microenvironment not the accumulated genetic mutations in cancer cells that determines tumor onset and malignant progression.106–109 Now, it is accepted that most of aging-associated cancers

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are systems disease with heterogeneity present at levels of the DNA, RNA, proteins, glycans, lipids, and metabolites.110–113 Therefore, cancers are complex diseases with heterogeneity at molecular, cellular, microenvironmental, and systems levels. If cancer is a complex and “personalized” disease, it means that the presence of universal cancer biomarkers with high sensitivity and specificity might not be the rule but the exception to the rule. The advancement in thinking of cancer and the advancement in cancer research technologies will be eventually allow the molecular signatures of specific cancer to be revealed and introduced into clinical practice for personalized care.

Acknowledgments This research was supported by the Natural Science Foundation of China (Grant 81672585), Key Technology Fund of Shandong Province (Grant 2016ZDJS07A07), the Taishan Scholar Fellowship, and the “Double First Class fund” of Shandong Province in China to L.Z.

Conflicts of interest The authors declare no conflict of interest.

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